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2020 – today
- 2024
[j69]Joe Benton, George Deligiannidis, Arnaud Doucet:
Error Bounds for Flow Matching Methods. Trans. Mach. Learn. Res. 2024 (2024)- [c129]Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis:
Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization. ICLR 2024 - [c128]Angus Phillips, Hai-Dang Dau, Michael John Hutchinson, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet:
Particle Denoising Diffusion Sampler. ICML 2024 - [i86]Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet:
Implicit Diffusion: Efficient Optimization through Stochastic Sampling. CoRR abs/2402.05468 (2024) - [i85]Angus Phillips, Hai-Dang Dau, Michael John Hutchinson, Valentin De Bortoli, George Deligiannidis
, Arnaud Doucet:
Particle Denoising Diffusion Sampler. CoRR abs/2402.06320 (2024) - [i84]Valentin De Bortoli, Michael J. Hutchinson, Peter Wirnsberger, Arnaud Doucet:
Target Score Matching. CoRR abs/2402.08667 (2024) - [i83]Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev, George-Cristian Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, Arnaud Doucet, David Budden, Yee Whye Teh, Razvan Pascanu, Nando de Freitas, Caglar Gulcehre:
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. CoRR abs/2402.19427 (2024) - [i82]Aleksandar Botev, Soham De, Samuel L. Smith, Anushan Fernando, George-Cristian Muraru, Ruba Haroun, Leonard Berrada, Razvan Pascanu, Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret, Sertan Girgin, Olivier Bachem, Alek Andreev, Kathleen Kenealy, Thomas Mesnard, Cassidy Hardin, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, Pouya Tafti, Armand Joulin, Noah Fiedel, Evan Senter, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, David Budden, Arnaud Doucet, Sharad Vikram, Adam Paszke, Trevor Gale, Sebastian Borgeaud, Charlie Chen, Andy Brock, Antonia Paterson, Jenny Brennan, Meg Risdal, Raj Gundluru, Nesh Devanathan, Paul Mooney, Nilay Chauhan, Phil Culliton, Luiz GUStavo Martins, Elisa Bandy, David Huntsperger, Glenn Cameron, Arthur Zucker, Tris Warkentin, Ludovic Peran, Minh Giang, Zoubin Ghahramani, Clément Farabet, Koray Kavukcuoglu, Demis Hassabis, Raia Hadsell, Yee Whye Teh, Nando de Frietas:
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. CoRR abs/2404.07839 (2024) - [i81]Yasin Abbasi-Yadkori, Ilja Kuzborskij, David Stutz, András György, Adam Fisch, Arnaud Doucet, Iuliya Beloshapka, Wei-Hung Weng, Yao-Yuan Yang, Csaba Szepesvári, Ali Taylan Cemgil, Nenad Tomasev:
Mitigating LLM Hallucinations via Conformal Abstention. CoRR abs/2405.01563 (2024) - [i80]Jiaxin Shi, Kehang Han, Zhe Wang, Arnaud Doucet, Michalis K. Titsias:
Simplified and Generalized Masked Diffusion for Discrete Data. CoRR abs/2406.04329 (2024) - [i79]Valentin De Bortoli, Iryna Korshunova, Andriy Mnih, Arnaud Doucet:
Schrödinger Bridge Flow for Unpaired Data Translation. CoRR abs/2409.09347 (2024) - 2023
- [j68]Kamélia Daudel, Joe Benton, Yuyang Shi, Arnaud Doucet:
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics. J. Mach. Learn. Res. 24: 243:1-243:83 (2023) - [j67]David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, Arnaud Doucet:
Conformal prediction under ambiguous ground truth. Trans. Mach. Learn. Res. 2023 (2023) - [c127]Eugenio Clerico, George Deligiannidis, Arnaud Doucet:
Wide stochastic networks: Gaussian limit and PAC-Bayesian training. ALT 2023: 447-470 - [c126]Francisco Vargas, Will Sussman Grathwohl, Arnaud Doucet:
Denoising Diffusion Samplers. ICLR 2023 - [c125]Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Sussman Grathwohl:
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. ICML 2023: 8489-8510 - [c124]Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola:
SE(3) diffusion model with application to protein backbone generation. ICML 2023: 40001-40039 - [c123]Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet:
Diffusion Schrödinger Bridge Matching. NeurIPS 2023 - [c122]Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Thomas Rainforth, Arnaud Doucet:
Trans-Dimensional Generative Modeling via Jump Diffusion Models. NeurIPS 2023 - [c121]Maxence Noble, Valentin De Bortoli, Arnaud Doucet, Alain Durmus:
Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters. NeurIPS 2023 - [c120]Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish, Jean-Francois Ton:
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits. NeurIPS 2023 - [c119]Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed:
A Unified Framework for U-Net Design and Analysis. NeurIPS 2023 - [i78]Rob Cornish, Muhammad Faaiz Taufiq, Arnaud Doucet, Chris C. Holmes:
Causal Falsification of Digital Twins. CoRR abs/2301.07210 (2023) - [i77]Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts:
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. CoRR abs/2301.08187 (2023) - [i76]Jason Yim, Brian L. Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, Tommi S. Jaakkola:
SE(3) diffusion model with application to protein backbone generation. CoRR abs/2302.02277 (2023) - [i75]Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Grathwohl:
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. CoRR abs/2302.11552 (2023) - [i74]Francisco Vargas, Will Grathwohl, Arnaud Doucet:
Denoising Diffusion Samplers. CoRR abs/2302.13834 (2023) - [i73]Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet:
Diffusion Schrödinger Bridge Matching. CoRR abs/2303.16852 (2023) - [i72]Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Tom Rainforth, Arnaud Doucet:
Trans-Dimensional Generative Modeling via Jump Diffusion Models. CoRR abs/2305.16261 (2023) - [i71]Maxence Noble, Valentin De Bortoli, Arnaud Doucet, Alain Durmus:
Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters. CoRR abs/2305.16557 (2023) - [i70]Joe Benton, George Deligiannidis, Arnaud Doucet:
Error Bounds for Flow Matching Methods. CoRR abs/2305.16860 (2023) - [i69]Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed:
A Unified Framework for U-Net Design and Analysis. CoRR abs/2305.19638 (2023) - [i68]David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy, Tatiana Matejovicova, Melih Barsbey, Patricia Strachan, Mike Schaekermann, Jan Freyberg, Rajeev V. Rikhye, Beverly Freeman, Javier Perez Matos, Umesh Telang, Dale R. Webster, Yuan Liu, Gregory S. Corrado, Yossi Matias, Pushmeet Kohli, Yun Liu, Arnaud Doucet, Alan Karthikesalingam:
Evaluating AI systems under uncertain ground truth: a case study in dermatology. CoRR abs/2307.02191 (2023) - [i67]David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, Arnaud Doucet:
Conformal prediction under ambiguous ground truth. CoRR abs/2307.09302 (2023) - [i66]Joe Benton, Valentin De Bortoli, Arnaud Doucet, George Deligiannidis:
Linear Convergence Bounds for Diffusion Models via Stochastic Localization. CoRR abs/2308.03686 (2023) - [i65]Çaglar Gülçehre, Tom Le Paine, Srivatsan Srinivasan, Ksenia Konyushkova, Lotte Weerts, Abhishek Sharma, Aditya Siddhant, Alex Ahern, Miaosen Wang, Chenjie Gu, Wolfgang Macherey, Arnaud Doucet, Orhan Firat, Nando de Freitas:
Reinforced Self-Training (ReST) for Language Modeling. CoRR abs/2308.08998 (2023) - [i64]Marin Vlastelica, Tatiana Lopez-Guevara, Kelsey R. Allen, Peter W. Battaglia, Arnaud Doucet, Kimberly L. Stachenfeld:
Diffusion Generative Inverse Design. CoRR abs/2309.02040 (2023) - [i63]Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish, Jean-Francois Ton:
Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits. CoRR abs/2312.01457 (2023) - 2022
- [j66]Maxime Vono, Daniel Paulin, Arnaud Doucet:
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting. J. Mach. Learn. Res. 23: 25:1-25:69 (2022) - [j65]Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet:
On Instrumental Variable Regression for Deep Offline Policy Evaluation. J. Mach. Learn. Res. 23: 302:1-302:40 (2022) - [j64]Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet:
COIN++: Neural Compression Across Modalities. Trans. Mach. Learn. Res. 2022 (2022) - [j63]Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet:
An empirical study of implicit regularization in deep offline RL. Trans. Mach. Learn. Res. 2022 (2022) - [c118]Eugenio Clerico, George Deligiannidis, Arnaud Doucet:
Conditionally Gaussian PAC-Bayes. AISTATS 2022: 2311-2329 - [c117]Emilien Dupont, Yee Whye Teh, Arnaud Doucet:
Generative Models as Distributions of Functions. AISTATS 2022: 2989-3015 - [c116]Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet, Benjamin Guedj:
On PAC-Bayesian reconstruction guarantees for VAEs. AISTATS 2022: 3066-3079 - [c115]Eugenio Clerico, Amitis Shidani, George Deligiannidis, Arnaud Doucet:
Chained generalisation bounds. COLT 2022: 4212-4257 - [c114]Angad Singh, Omar Makhlouf, Maximilian Igl, João V. Messias, Arnaud Doucet, Shimon Whiteson:
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving. CoRL 2022: 1168-1177 - [c113]David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet:
Learning Optimal Conformal Classifiers. ICLR 2022 - [c112]Alexander G. de G. Matthews, Michael Arbel, Danilo Jimenez Rezende, Arnaud Doucet:
Continual Repeated Annealed Flow Transport Monte Carlo. ICML 2022: 15196-15219 - [c111]Liyuan Xu, Yutian Chen, Arnaud Doucet, Arthur Gretton:
Importance Weighted Kernel Bayes' Rule. ICML 2022: 24524-24538 - [c110]Valentin De Bortoli, Emile Mathieu, Michael J. Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet:
Riemannian Score-Based Generative Modelling. NeurIPS 2022 - [c109]Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, Arnaud Doucet:
A Continuous Time Framework for Discrete Denoising Models. NeurIPS 2022 - [c108]Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
Towards Learning Universal Hyperparameter Optimizers with Transformers. NeurIPS 2022 - [c107]Arnaud Doucet, Will Grathwohl, Alexander G. de G. Matthews, Heiko Strathmann:
Score-Based Diffusion meets Annealed Importance Sampling. NeurIPS 2022 - [c106]Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts:
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. NeurIPS 2022 - [c105]Muhammad Faaiz Taufiq, Jean-Francois Ton, Rob Cornish, Yee Whye Teh, Arnaud Doucet:
Conformal Off-Policy Prediction in Contextual Bandits. NeurIPS 2022 - [c104]Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes:
Mitigating statistical bias within differentially private synthetic data. UAI 2022: 696-705 - [c103]Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet:
Conditional simulation using diffusion Schrödinger bridges. UAI 2022: 1792-1802 - [i62]Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet:
COIN++: Data Agnostic Neural Compression. CoRR abs/2201.12904 (2022) - [i61]Alexander G. de G. Matthews, Michael Arbel, Danilo J. Rezende, Arnaud Doucet:
Continual Repeated Annealed Flow Transport Monte Carlo. CoRR abs/2201.13117 (2022) - [i60]Liyuan Xu, Yutian Chen, Arnaud Doucet, Arthur Gretton:
Importance Weighting Approach in Kernel Bayes' Rule. CoRR abs/2202.02474 (2022) - [i59]Valentin De Bortoli, Emile Mathieu, Michael J. Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet:
Riemannian Score-Based Generative Modeling. CoRR abs/2202.02763 (2022) - [i58]Badr-Eddine Chérief-Abdellatif, Yuyang Shi, Arnaud Doucet, Benjamin Guedj:
On PAC-Bayesian reconstruction guarantees for VAEs. CoRR abs/2202.11455 (2022) - [i57]Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet:
Conditional Simulation Using Diffusion Schrödinger Bridges. CoRR abs/2202.13460 (2022) - [i56]Eugenio Clerico, Amitis Shidani, George Deligiannidis, Arnaud Doucet:
Chained Generalisation Bounds. CoRR abs/2203.00977 (2022) - [i55]Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Qiuyi Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas:
Towards Learning Universal Hyperparameter Optimizers with Transformers. CoRR abs/2205.13320 (2022) - [i54]Andrew Campbell, Joe Benton, Valentin De Bortoli, Tom Rainforth, George Deligiannidis, Arnaud Doucet:
A Continuous Time Framework for Discrete Denoising Models. CoRR abs/2205.14987 (2022) - [i53]Muhammad Faaiz Taufiq, Jean-Francois Ton, Robert Cornish, Yee Whye Teh, Arnaud Doucet:
Conformal Off-Policy Prediction in Contextual Bandits. CoRR abs/2206.04405 (2022) - [i52]Amitis Shidani, George Deligiannidis, Arnaud Doucet:
Ranking in Contextual Multi-Armed Bandits. CoRR abs/2207.00109 (2022) - [i51]Çaglar Gülçehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matt Hoffman, Razvan Pascanu, Arnaud Doucet:
An Empirical Study of Implicit Regularization in Deep Offline RL. CoRR abs/2207.02099 (2022) - [i50]James Thornton, Michael J. Hutchinson, Emile Mathieu, Valentin De Bortoli, Yee Whye Teh, Arnaud Doucet:
Riemannian Diffusion Schrödinger Bridge. CoRR abs/2207.03024 (2022) - [i49]Arnaud Doucet, Will Grathwohl, Alexander G. de G. Matthews, Heiko Strathmann:
Score-Based Diffusion meets Annealed Importance Sampling. CoRR abs/2208.07698 (2022) - [i48]Eugenio Clerico, George Deligiannidis, Benjamin Guedj, Arnaud Doucet:
A PAC-Bayes bound for deterministic classifiers. CoRR abs/2209.02525 (2022) - [i47]Francesca R. Crucinio, Valentin De Bortoli, Arnaud Doucet, Adam M. Johansen:
Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows. CoRR abs/2209.09936 (2022) - [i46]Angus Phillips, Thomas Seror, Michael J. Hutchinson, Valentin De Bortoli, Arnaud Doucet, Emile Mathieu:
Spectral Diffusion Processes. CoRR abs/2209.14125 (2022) - [i45]Kamélia Daudel, Joe Benton, Yuyang Shi, Arnaud Doucet:
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics. CoRR abs/2210.06226 (2022) - [i44]Pierre Glaser, Michael Arbel, Arnaud Doucet, Arthur Gretton:
Maximum Likelihood Learning of Energy-Based Models for Simulation-Based Inference. CoRR abs/2210.14756 (2022) - [i43]Pierre H. Richemond, Sander Dieleman, Arnaud Doucet:
Categorical SDEs with Simplex Diffusion. CoRR abs/2210.14784 (2022) - [i42]Joe Benton, Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet:
From Denoising Diffusions to Denoising Markov Models. CoRR abs/2211.03595 (2022) - [i41]Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H. Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, Curtis Hawthorne, Rémi Leblond, Will Grathwohl, Jonas Adler:
Continuous diffusion for categorical data. CoRR abs/2211.15089 (2022) - [i40]Angad Singh, Omar Makhlouf, Maximilian Igl, João V. Messias, Arnaud Doucet, Shimon Whiteson:
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving. CoRR abs/2212.06968 (2022) - 2021
- [j62]Philippe Gagnon, Arnaud Doucet:
Nonreversible Jump Algorithms for Bayesian Nested Model Selection. J. Comput. Graph. Stat. 30(2): 312-323 (2021) - [j61]Vladislav Z. B. Tadic, Arnaud Doucet:
Bias of Particle Approximations to Optimal Filter Derivative. SIAM J. Control. Optim. 59(1): 727-748 (2021) - [j60]Adrian N. Bishop, Arnaud Doucet:
Network Consensus in the Wasserstein Metric Space of Probability Measures. SIAM J. Control. Optim. 59(5): 3261-3277 (2021) - [j59]Chris J. Maddison, Daniel Paulin, Yee Whye Teh, Arnaud Doucet:
Dual Space Preconditioning for Gradient Descent. SIAM J. Optim. 31(1): 991-1016 (2021) - [j58]Vladislav Z. B. Tadic, Arnaud Doucet:
Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation. IEEE Trans. Inf. Theory 67(3): 1825-1848 (2021) - [c102]Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau:
Stable ResNet. AISTATS 2021: 1324-1332 - [c101]Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
The Curse of Depth in Kernel Regime. ICBINB@NeurIPS 2021: 41-47 - [c100]Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh:
Robust Pruning at Initialization. ICLR 2021 - [c99]Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton:
Learning Deep Features in Instrumental Variable Regression. ICLR 2021 - [c98]Michael Arbel, Alexander G. de G. Matthews, Arnaud Doucet:
Annealed Flow Transport Monte Carlo. ICML 2021: 318-330 - [c97]Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet:
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport. ICML 2021: 2100-2111 - [c96]Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison:
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. ICML 2021: 9136-9147 - [c95]Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov:
Monte Carlo Variational Auto-Encoders. ICML 2021: 10247-10257 - [c94]Achille Thin, Yazid Janati El Idrissi, Sylvain Le Corff, Charles Ollion, Eric Moulines, Arnaud Doucet, Alain Durmus, Christian X. Robert:
NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform. NeurIPS 2021: 17060-17071 - [c93]Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet:
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling. NeurIPS 2021: 17695-17709 - [c92]Andrew Campbell, Yuyang Shi, Thomas Rainforth, Arnaud Doucet:
Online Variational Filtering and Parameter Learning. NeurIPS 2021: 18633-18645 - [c91]Anthony L. Caterini, Robert Cornish, Dino Sejdinovic, Arnaud Doucet:
Variational inference with continuously-indexed normalizing flows. UAI 2021: 44-53 - [c90]Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet:
Unbiased gradient estimation for variational auto-encoders using coupled Markov chains. UAI 2021: 707-717 - [i39]Emilien Dupont, Yee Whye Teh, Arnaud Doucet:
Generative Models as Distributions of Functions. CoRR abs/2102.04776 (2021) - [i38]Michael Arbel, Alexander G. de G. Matthews, Arnaud Doucet:
Annealed Flow Transport Monte Carlo. CoRR abs/2102.07501 (2021) - [i37]Adrien Corenflos, James Thornton, Arnaud Doucet, George Deligiannidis:
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport. CoRR abs/2102.07850 (2021) - [i36]Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison:
Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding. CoRR abs/2102.11086 (2021) - [i35]Emilien Dupont, Adam Golinski, Milad Alizadeh, Yee Whye Teh, Arnaud Doucet:
COIN: COmpression with Implicit Neural representations. CoRR abs/2103.03123 (2021) - [i34]Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet:
On Instrumental Variable Regression for Deep Offline Policy Evaluation. CoRR abs/2105.10148 (2021) - [i33]Valentin De Bortoli, James Thornton, Jeremy Heng, Arnaud Doucet:
Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling. CoRR abs/2106.01357 (2021) - [i32]Eugenio Clerico, George Deligiannidis, Arnaud Doucet:
Wide stochastic networks: Gaussian limit and PAC-Bayesian training. CoRR abs/2106.09798 (2021) - [i31]Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov:
Monte Carlo Variational Auto-Encoders. CoRR abs/2106.15921 (2021) - [i30]George Deligiannidis, Valentin De Bortoli, Arnaud Doucet:
Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure. CoRR abs/2108.08129 (2021) - [i29]Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes:
Bias Mitigated Learning from Differentially Private Synthetic Data: A Cautionary Tale. CoRR abs/2108.10934 (2021) - [i28]David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet:
Learning Optimal Conformal Classifiers. CoRR abs/2110.09192 (2021) - [i27]Eugenio Clerico, George Deligiannidis, Arnaud Doucet:
Conditional Gaussian PAC-Bayes. CoRR abs/2110.11886 (2021) - [i26]Andrew Campbell, Yuyang Shi, Tom Rainforth, Arnaud Doucet:
Online Variational Filtering and Parameter Learning. CoRR abs/2110.13549 (2021) - [i25]Valentin De Bortoli, Arnaud Doucet, Jeremy Heng, James Thornton:
Simulating Diffusion Bridges with Score Matching. CoRR abs/2111.07243 (2021) - 2020
- [c89]Robert Cornish, Anthony L. Caterini, George Deligiannidis, Arnaud Doucet:
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows. ICML 2020: 2133-2143 - [c88]Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman, Nando de Freitas:
Modular Meta-Learning with Shrinkage. NeurIPS 2020 - [i24]Soufiane Hayou, Jean-Francois Ton, Arnaud Doucet, Yee Whye Teh:
Pruning untrained neural networks: Principles and Analysis. CoRR abs/2002.08797 (2020) - [i23]Anthony L. Caterini, Robert Cornish, Dino Sejdinovic, Arnaud Doucet:
Variational Inference with Continuously-Indexed Normalizing Flows. CoRR abs/2007.05426 (2020) - [i22]Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet:
Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains. CoRR abs/2010.01845 (2020) - [i21]Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton:
Learning Deep Features in Instrumental Variable Regression. CoRR abs/2010.07154 (2020) - [i20]Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau:
Stable ResNet. CoRR abs/2010.12859 (2020)
2010 – 2019
- 2019
- [j57]Vladislav Z. B. Tadic, Arnaud Doucet:
Analyticity of Entropy Rates of Continuous-State Hidden Markov Models. IEEE Trans. Inf. Theory 65(12): 7950-7975 (2019) - [c87]Sebastian M. Schmon, Arnaud Doucet, George Deligiannidis:
Bernoulli Race Particle Filters. AISTATS 2019: 2350-2358 - [c86]Lawrece Middleton, George Deligiannidis, Arnaud Doucet, Pierre E. Jacob:
Unbiased Smoothing using Particle Independent Metropolis-Hastings. AISTATS 2019: 2378-2387 - [c85]Vladislav Z. B. Tadic, Arnaud Doucet:
Stability of Optimal Filter Higher-Order Derivatives. CDC 2019: 1644-1649 - [c84]Robert Cornish, Paul Vanetti, Alexandre Bouchard-Côté, George Deligiannidis, Arnaud Doucet:
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets. ICML 2019: 1351-1360 - [c83]Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
On the Impact of the Activation function on Deep Neural Networks Training. ICML 2019: 2672-2680 - [c82]Alexander Y. Shestopaloff, Arnaud Doucet:
Replica Conditional Sequential Monte Carlo. ICML 2019: 5749-5757 - [c81]Vladislav Z. B. Tadic, Arnaud Doucet:
Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation. ISIT 2019: 887-891 - [c80]Emilien Dupont, Arnaud Doucet, Yee Whye Teh:
Augmented Neural ODEs. NeurIPS 2019: 3134-3144 - [i19]Robert Cornish, Paul Vanetti, Alexandre Bouchard-Côté, George Deligiannidis, Arnaud Doucet:
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets. CoRR abs/1901.09881 (2019) - [i18]Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
On the Impact of the Activation Function on Deep Neural Networks Training. CoRR abs/1902.06853 (2019) - [i17]Emilien Dupont, Arnaud Doucet, Yee Whye Teh:
Augmented Neural ODEs. CoRR abs/1904.01681 (2019) - [i16]Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
Training Dynamics of Deep Networks using Stochastic Gradient Descent via Neural Tangent Kernel. CoRR abs/1905.13654 (2019) - [i15]Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas:
Modular Meta-Learning with Shrinkage. CoRR abs/1909.05557 (2019) - [i14]Robert Cornish, Anthony L. Caterini, George Deligiannidis, Arnaud Doucet:
Localised Generative Flows. CoRR abs/1909.13833 (2019) - 2018
- [c79]Anthony L. Caterini, Arnaud Doucet, Dino Sejdinovic:
Hamiltonian Variational Auto-Encoder. NeurIPS 2018: 8178-8188 - [i13]Soufiane Hayou, Arnaud Doucet, Judith Rousseau:
On the Selection of Initialization and Activation Function for Deep Neural Networks. CoRR abs/1805.08266 (2018) - [i12]Anthony L. Caterini, Arnaud Doucet, Dino Sejdinovic:
Hamiltonian Variational Auto-Encoder. CoRR abs/1805.11328 (2018) - [i11]Vladislav Z. B. Tadic, Arnaud Doucet:
Analyticity of Entropy Rates of Continuous-State Hidden Markov Models. CoRR abs/1806.09589 (2018) - [i10]Chris J. Maddison, Daniel Paulin, Yee Whye Teh, Brendan O'Donoghue, Arnaud Doucet:
Hamiltonian Descent Methods. CoRR abs/1809.05042 (2018) - 2017
- [j56]François Caron, Willie Neiswanger, Frank D. Wood, Arnaud Doucet, Manuel Davy:
Generalized Pólya Urn for Time-Varying Pitman-Yor Processes. J. Mach. Learn. Res. 18: 27:1-27:32 (2017) - [j55]Alexandre Bouchard-Côté, Arnaud Doucet, Andrew Roth:
Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models. J. Mach. Learn. Res. 18: 28:1-28:39 (2017) - [j54]Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes:
On Markov chain Monte Carlo methods for tall data. J. Mach. Learn. Res. 18: 47:1-47:43 (2017) - [c78]Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Arnaud Doucet, Andriy Mnih, Yee Whye Teh:
Particle Value Functions. ICLR (Workshop) 2017 - [c77]Andrei-Cristian Barbos, Francois Caron, Jean-François Giovannelli, Arnaud Doucet:
Clone MCMC: Parallel High-Dimensional Gaussian Gibbs Sampling. NIPS 2017: 5020-5028 - [c76]Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Mohammad Norouzi, Andriy Mnih, Arnaud Doucet, Yee Whye Teh:
Filtering Variational Objectives. NIPS 2017: 6573-6583 - [i9]Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Arnaud Doucet, Andriy Mnih, Yee Whye Teh:
Particle Value Functions. CoRR abs/1703.05820 (2017) - [i8]Chris J. Maddison, Dieterich Lawson, George Tucker, Nicolas Heess, Mohammad Norouzi, Andriy Mnih, Arnaud Doucet, Yee Whye Teh:
Filtering Variational Objectives. CoRR abs/1705.09279 (2017) - 2016
- [c75]Tom Rainforth, Christian A. Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem van de Meent, Arnaud Doucet, Frank D. Wood:
Interacting Particle Markov Chain Monte Carlo. ICML 2016: 2616-2625 - 2015
- [j53]Pierre Del Moral, Arnaud Doucet, Sumeetpal S. Singh:
Uniform Stability of a Particle Approximation of the Optimal Filter Derivative. SIAM J. Control. Optim. 53(3): 1278-1304 (2015) - [c74]Thibaut Liénart, Yee Whye Teh, Arnaud Doucet:
Expectation Particle Belief Propagation. NIPS 2015: 3609-3617 - [i7]Thibaut Liénart, Yee Whye Teh, Arnaud Doucet:
Expectation Particle Belief Propagation. CoRR abs/1506.05934 (2015) - 2014
- [j52]Ido Nevat, Gareth W. Peters, Arnaud Doucet, Jinhong Yuan:
Joint Channel and Doppler Offset Estimation in Dynamic Cooperative Relay Networks. IEEE Trans. Wirel. Commun. 13(12): 6570-6579 (2014) - [c73]Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes:
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach. ICML 2014: 405-413 - [c72]Marco Cuturi, Arnaud Doucet:
Fast Computation of Wasserstein Barycenters. ICML 2014: 685-693 - [c71]Brooks Paige, Frank D. Wood, Arnaud Doucet, Yee Whye Teh:
Asynchronous Anytime Sequential Monte Carlo. NIPS 2014: 3410-3418 - 2013
- [j51]Tomoaki Kimura, T. Tokuda, Yohei Nakada, T. Nokajima, Takashi Matsumoto, Arnaud Doucet:
Expectation-maximization algorithms for inference in Dirichlet processes mixture. Pattern Anal. Appl. 16(1): 55-67 (2013) - [j50]Arnaud Doucet, Christian P. Robert:
Introduction to Special Issue on Monte Carlo Methods in Statistics. ACM Trans. Model. Comput. Simul. 23(1): 1:1-1:2 (2013) - [i6]Christophe Andrieu, Nando de Freitas, Arnaud Doucet:
Reversible Jump MCMC Simulated Annealing for Neural Networks. CoRR abs/1301.3833 (2013) - [i5]Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell:
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. CoRR abs/1301.3853 (2013) - 2012
- [j49]Francois Caron, Arnaud Doucet, Raphael Gottardo:
On-line changepoint detection and parameter estimation with application to genomic data. Stat. Comput. 22(2): 579-595 (2012) - [j48]Pierre Del Moral, Arnaud Doucet, Ajay Jasra:
An adaptive sequential Monte Carlo method for approximate Bayesian computation. Stat. Comput. 22(5): 1009-1020 (2012) - [j47]Nikolaos Kantas, Sumeetpal S. Singh, Arnaud Doucet:
Distributed Maximum Likelihood for Simultaneous Self-Localization and Tracking in Sensor Networks. IEEE Trans. Signal Process. 60(10): 5038-5047 (2012) - [i4]Matthias Hoffman, Hendrik Kück, Nando de Freitas, Arnaud Doucet:
New inference strategies for solving Markov Decision Processes using reversible jump MCMC. CoRR abs/1205.2643 (2012) - [i3]Nikolaos Kantas, Sumeetpal S. Singh, Arnaud Doucet:
Distributed Maximum Likelihood for Simultaneous Self-localization and Tracking in Sensor Networks. CoRR abs/1206.4221 (2012) - [i2]Mike Klaas, Nando de Freitas, Arnaud Doucet:
Toward Practical N2 Monte Carlo: the Marginal Particle Filter. CoRR abs/1207.1396 (2012) - 2011
- [j46]Seokhwan Jo, Chang D. Yoo, Arnaud Doucet:
Melody Tracking Based on Sequential Bayesian Model. IEEE J. Sel. Top. Signal Process. 5(6): 1216-1227 (2011) - [j45]Francois Caron, Pierre Del Moral, Arnaud Doucet, Michele Pace:
Particle Approximation of the Intensity Measures of a Spatial Branching Point Process Arising in Multitarget Tracking. SIAM J. Control. Optim. 49(4): 1766-1792 (2011) - [c70]Vladislav Z. B. Tadic, Arnaud Doucet:
Asymptotic bias of stochastic gradient search. CDC/ECC 2011: 722-727 - 2010
- [j44]Arnaud Doucet, Adam M. Johansen, Vladislav Z. B. Tadic:
On solving integral equations using Markov chain Monte Carlo methods. Appl. Math. Comput. 216(10): 2869-2880 (2010) - [j43]Pierre Minvielle, Arnaud Doucet, Alan Marrs, Simon Maskell:
A Bayesian approach to joint tracking and identification of geometric shapes in video sequences. Image Vis. Comput. 28(1): 111-123 (2010) - [j42]Audrey Giremus, Jean-Yves Tourneret, Arnaud Doucet:
A Fixed-Lag Particle Filter for the Joint Detection/Compensation of Interference Effects in GPS Navigation. IEEE Trans. Signal Process. 58(12): 6066-6079 (2010) - [i1]Ido Nevat, Gareth W. Peters, Arnaud Doucet, Jinhong Yuan:
Channel Tracking for Relay Networks via Adaptive Particle MCMC. CoRR abs/1006.3151 (2010)
2000 – 2009
- 2009
- [j41]Ruben Martinez-Cantin, Nando de Freitas, Eric Brochu, José A. Castellanos, Arnaud Doucet:
A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot. Auton. Robots 27(2): 93-103 (2009) - [j40]Shahzia Anjum, Arnaud Doucet, Christopher C. Holmes:
A boosting approach to structure learning of graphs with and without prior knowledge. Bioinform. 25(22): 2929-2936 (2009) - [j39]Smita Sadhu, Shovan Bhaumik, Arnaud Doucet, Tapan Kumar Ghoshal:
Particle-method-based formulation of risk-sensitive filter. Signal Process. 89(3): 314-319 (2009) - [c69]Hendrik Kück, Matt Hoffman, Arnaud Doucet, Nando de Freitas:
Inference and Learning for Active Sensing, Experimental Design and Control. IbPRIA 2009: 1-10 - [c68]Francois Caron, Arnaud Doucet:
Bayesian Nonparametric Models on Decomposable Graphs. NIPS 2009: 225-233 - [c67]Matthias Hoffman, Hendrik Kück, Nando de Freitas, Arnaud Doucet:
New inference strategies for solving Markov Decision Processes using reversible jump MCMC. UAI 2009: 223-231 - [c66]Matthew Hoffman, Nando de Freitas, Arnaud Doucet, Jan Peters:
An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward. AISTATS 2009: 232-239 - 2008
- [j38]Ajay Jasra, Arnaud Doucet, David A. Stephens, Christopher C. Holmes:
Interacting sequential Monte Carlo samplers for trans-dimensional simulation. Comput. Stat. Data Anal. 52(4): 1765-1791 (2008) - [j37]Adam M. Johansen, Arnaud Doucet, Manuel Davy:
Particle methods for maximum likelihood estimation in latent variable models. Stat. Comput. 18(1): 47-57 (2008) - [j36]Francois Caron, Manuel Davy, Arnaud Doucet, Emmanuel Duflos, Philippe Vanheeghe:
Bayesian Inference for Linear Dynamic Models With Dirichlet Process Mixtures. IEEE Trans. Signal Process. 56(1): 71-84 (2008) - [c65]Francois Caron, Arnaud Doucet:
Sparse Bayesian nonparametric regression. ICML 2008: 88-95 - 2007
- [j35]Sumeetpal S. Singh, Nikolaos Kantas, Ba-Ngu Vo, Arnaud Doucet, Robin J. Evans:
Simulation-based optimal sensor scheduling with application to observer trajectory planning. Autom. 43(5): 817-830 (2007) - [j34]Sumeetpal S. Singh, Vladislav Z. B. Tadic, Arnaud Doucet:
A policy gradient method for semi-Markov decision processes with application to call admission control. Eur. J. Oper. Res. 178(3): 808-818 (2007) - [j33]Simon I. Hill, Arnaud Doucet:
A Framework for Kernel-Based Multi-Category Classification. J. Artif. Intell. Res. 30: 525-564 (2007) - [j32]Hassan Ali, Arnaud Doucet, Dino Isa Amshah:
GSR: A New Genetic Algorithm for Improving Source and Channel Estimates. IEEE Trans. Circuits Syst. I Regul. Pap. 54-I(5): 1088-1098 (2007) - [c64]Edmund S. Jackson, Manuel Davy, Arnaud Doucet, William J. Fitzgerald:
Bayesian Unsupervised Signal Classification by Dirichlet Process Mixtures of Gaussian Processes. ICASSP (3) 2007: 1077-1080 - [c63]Vladislav Z. B. Tadic, Arnaud Doucet:
A Monte Carlo Algorithm for Optimal Quantization in Hidden Markov Models. ISIT 2007: 1121-1125 - [c62]Matt Hoffman, Arnaud Doucet, Nando de Freitas, Ajay Jasra:
Bayesian Policy Learning with Trans-Dimensional MCMC. NIPS 2007: 665-672 - [c61]Ruben Martinez-Cantin, Nando de Freitas, Arnaud Doucet, José A. Castellanos:
Active Policy Learning for Robot Planning and Exploration under Uncertainty. Robotics: Science and Systems 2007 - [c60]Francois Caron, Manuel Davy, Arnaud Doucet:
Generalized Polya Urn for Time-varying Dirichlet Process Mixtures. UAI 2007: 33-40 - 2006
- [c59]George Poyiadjis, Sumeetpal S. Singh, Arnaud Doucet:
Gradient-free maximum likelihood parameter estimation with particle filters. ACC 2006: 1-6 - [c58]Francois Caron, Manuel Davy, Arnaud Doucet, Emmanuel Duflos, Philippe Vanheeghe:
Bayesian Inference for Dynamic Models with Dirichlet Process Mixtures. FUSION 2006: 1-8 - [c57]Nikolaos Kantas, Sumeetpal S. Singh, Arnaud Doucet:
A Distributed Recursive Maximum Likelihood Implementation for Sensor Registration. FUSION 2006: 1-8 - [c56]George Poyiadjis, Sumeetpal S. Singh, Arnaud Doucet:
Particle Filter as A Controlled Markov Chain For On-Line Parameter Estimation in General State Space Models. ICASSP (3) 2006: 329-332 - [c55]Arnaud Doucet, Luis Montesano, Ajay Jasra:
Optimal Filtering For Partially Observed Point Processes Using Trans-Dimensional Sequential Monte Carlo. ICASSP (5) 2006: 597-600 - [c54]Adam M. Johansen, Arnaud Doucet, Manuel Davy:
Maximum Likelihood Parameter Estimation for Latent Variable Models Using Sequential Monte Carlo. ICASSP (3) 2006: 640-643 - [c53]Mike Klaas, Mark Briers, Nando de Freitas, Arnaud Doucet, Simon Maskell, Dustin Lang:
Fast particle smoothing: if I had a million particles. ICML 2006: 481-488 - [c52]Abhijeet Ghosh, Arnaud Doucet, Wolfgang Heidrich:
Sequential Sampling for Dynamic Environment Map Illumination. Rendering Techniques 2006: 115-126 - [c51]Abhijeet Ghosh, Arnaud Doucet, Wolfgang Heidrich:
Sequential sampling for dynamic environment maps. SIGGRAPH Sketches 2006: 157 - 2005
- [j31]Arnaud Doucet, Xiaodong Wang:
Monte Carlo methods for signal processing: a review in the statistical signal processing context. IEEE Signal Process. Mag. 22(6): 152-170 (2005) - [c50]Christophe Andrieu, Arnaud Doucet, Vladislav Z. B. Tadic:
On-Line Parameter Estimation in General State-Space Models. CDC/ECC 2005: 332-337 - [c49]Sumeetpal S. Singh, Nikolaos Kantas, Arnaud Doucet, Ba-Ngu Vo, Robin J. Evans:
Simulation-Based Optimal Sensor Scheduling with Application to Observer Trajectory Planning. CDC/ECC 2005: 7296-7301 - [c48]Arnaud Doucet, Stéphane Sénécal, Tomoko Matsui:
Space alternating data augmentation: application to finite mixture of Gaussians and speaker recognition. ICASSP (4) 2005: 713-716 - [c47]George Poyiadjis, Arnaud Doucet, Sumeetpal S. Singh:
Particle methods for optimal filter derivative: application to parameter estimation. ICASSP (5) 2005: 925-928 - [c46]Simon I. Hill, Arnaud Doucet:
Adapting two-class support vector classification methods to many class problems. ICML 2005: 313-320 - [c45]Zaifei Liu, Arnaud Doucet:
Joint Bayesian model selection and blind equalization of ISI channels. ISSPA 2005: 479-482 - [c44]Mike Klaas, Nando de Freitas, Arnaud Doucet:
Toward Practical N2 Monte Carlo: the Marginal Particle Filter. UAI 2005: 308-315 - 2004
- [j30]Hassan Ali, Arnaud Doucet, Yingbo Hua:
Blind SOS subspace channel estimation and equalization techniques exploiting spatial diversity in OFDM systems. Digit. Signal Process. 14(2): 171-202 (2004) - [j29]Petar M. Djuric, Simon J. Godsill, Arnaud Doucet:
Editorial. EURASIP J. Adv. Signal Process. 2004(15): 2239-2241 (2004) - [j28]Elena Punskaya, Arnaud Doucet, William J. Fitzgerald:
Particle Filtering for Joint Symbol and Code Delay Estimation in DS Spread Spectrum Systems in Multipath Environment. EURASIP J. Adv. Signal Process. 2004(15): 2306-2314 (2004) - [j27]Christophe Andrieu, Arnaud Doucet, Sumeetpal S. Singh, Vladislav Z. B. Tadic:
Particle methods for change detection, system identification, and control. Proc. IEEE 92(3): 423-438 (2004) - [c43]Arnaud Doucet, Stéphane Sénécal:
Fixed-lag sequential Monte Carlo. EUSIPCO 2004: 861-864 - [c42]Audrey Giremus, Arnaud Doucet, Anne-Christine Escher, Jean-Yves Tourneret:
Nonlinear filtering approaches for INS/GPS integration. EUSIPCO 2004: 873-876 - [c41]Audrey Giremus, Arnaud Doucet, Vincent Calmettes, Jean-Yves Tourneret:
A Rao-Blackwellized particle filter for INS/GPS integration. ICASSP (3) 2004: 964-967 - [c40]Zaifei Liu, Arnaud Doucet, Sumeetpal S. Singh:
The cross-entropy method for blind multiuser detection. ISIT 2004: 510 - 2003
- [j26]Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan:
An Introduction to MCMC for Machine Learning. Mach. Learn. 50(1-2): 5-43 (2003) - [j25]Manuel Davy, Arnaud Doucet:
Copulas: a new insight into positive time-frequency distributions. IEEE Signal Process. Lett. 10(7): 215-218 (2003) - [j24]Christophe Andrieu, Manuel Davy, Arnaud Doucet:
Efficient particle filtering for jump Markov systems. Application to time-varying autoregressions. IEEE Trans. Signal Process. 51(7): 1762-1770 (2003) - [j23]Bin Dong, Xiaodong Wang, Arnaud Doucet:
A new class of soft MIMO demodulation algorithms. IEEE Trans. Signal Process. 51(11): 2752-2763 (2003) - [c39]Vladislav Z. B. Tadic, Arnaud Doucet, Sumeetpal S. Singh:
Two time-scale stochastic approximation for constrained stochastic optimization and constrained Markov decision problems. ACC 2003: 4736-4741 - [c38]Bin Dong, Xiaodong Wang, Arnaud Doucet:
Sampling-based near-optimal MIMO demodulation algorithms. CDC 2003: 4214-4219 - [c37]Sumeetpal S. Singh, Ba-Ngu Vo, Arnaud Doucet, Robin J. Evans:
Stochastic approximation for optimal observer trajectory planning. CDC 2003: 6313-6318 - [c36]Christophe Andrieu, Arnaud Doucet:
Online expectation-maximization type algorithms for parameter estimation in general state space models. ICASSP (6) 2003: 69-72 - [c35]Elena Punskaya, Arnaud Doucet, William J. Fitzgerald:
Particle filtering for joint symbol and parameter estimation in DS spread spectrum systems. ICASSP (4) 2003: 441-444 - [c34]Bao Ling Chan, Arnaud Doucet, Vladislav Z. B. Tadic:
Optimisation of particle filters using simultaneous perturbation stochastic approximation. ICASSP (6) 2003: 681-684 - [c33]Jaco Vermaak, Arnaud Doucet, Patrick Pérez:
Maintaining Multi-Modality through Mixture Tracking. ICCV 2003: 1110-1116 - [c32]Jaco Vermaak, Simon J. Godsill, Arnaud Doucet:
Sequential Bayesian Kernel Regression. NIPS 2003: 113-120 - 2002
- [j22]Arnaud Doucet, Simon J. Godsill, Christian P. Robert:
Marginal maximum a posteriori estimation using Markov chain Monte Carlo. Stat. Comput. 12(1): 77-84 (2002) - [j21]Manuel Davy, Arthur Gretton, Arnaud Doucet, Peter J. W. Rayner:
Optimized support vector machines for nonstationary signal classification. IEEE Signal Process. Lett. 9(12): 442-445 (2002) - [j20]Jaco Vermaak, Christophe Andrieu, Arnaud Doucet, Simon J. Godsill:
Particle methods for Bayesian modeling and enhancement of speech signals. IEEE Trans. Speech Audio Process. 10(3): 173-185 (2002) - [j19]William Fong, Simon J. Godsill, Arnaud Doucet, Mike West:
Monte Carlo smoothing with application to audio signal enhancement. IEEE Trans. Signal Process. 50(2): 438-449 (2002) - [j18]Dan Crisan, Arnaud Doucet:
A survey of convergence results on particle filtering methods for practitioners. IEEE Trans. Signal Process. 50(3): 736-746 (2002) - [j17]Elena Punskaya, Christophe Andrieu, Arnaud Doucet, William J. Fitzgerald:
Bayesian curve fitting using MCMC with applications to signal segmentation. IEEE Trans. Signal Process. 50(3): 747-758 (2002) - [c31]Arnaud Doucet, Vladislav Z. B. Tadic:
On-line optimization of sequential Monte Carlo methods using stochastic approximation. ACC 2002: 2565-2570 - [c30]Vladislav Z. B. Tadic, Arnaud Doucet:
Exponential forgetting and geometric ergodicity in state-space models. CDC 2002: 2231-2235 - [c29]Christophe Andrieu, Manuel Davy, Arnaud Doucet:
A particle filtering technique for Jump Markov Systems. EUSIPCO 2002: 1-4 - [c28]Elena Punskaya, Arnaud Doucet, William J. Fitzgerald:
On the use and misuse of particle filtering in digital communications. EUSIPCO 2002: 1-4 - [c27]Sumetpal Singh, Vladislav Z. B. Tadic, Arnaud Doucet:
A policy gradient method for SMDPs with application to call admission control. ICARCV 2002: 1268-1274 - [c26]Christophe Andrieu, Manuel Davy, Arnaud Doucet:
Efficient particle filtering for Jump Markov Systems. ICASSP 2002: 1625-1628 - [c25]Shien-Shin Tham, Arnaud Doucet, Kotagiri Ramamohanarao:
Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo. ICML 2002: 634-641 - 2001
- [j16]Christophe Andrieu, Arnaud Doucet:
Optimal Estimation of Amplitude and Phase Modulated Signals. Monte Carlo Methods Appl. 7(1-2): 1-14 (2001) - [j15]Christophe Andrieu, Nando de Freitas, Arnaud Doucet:
Robust Full Bayesian Learning for Radial Basis Networks. Neural Comput. 13(10): 2359-2407 (2001) - [j14]Christophe Andrieu, Petar M. Djuric, Arnaud Doucet:
Model selection by MCMC computation. Signal Process. 81(1): 19-37 (2001) - [j13]Elena Punskaya, Christophe Andrieu, Arnaud Doucet, William J. Fitzgerald:
Particle filtering for demodulation in fading channels with non-Gaussian additive noise. IEEE Trans. Commun. 49(4): 579-582 (2001) - [j12]Christophe Andrieu, Eric Barat, Arnaud Doucet:
Bayesian deconvolution of noisy filtered point processes. IEEE Trans. Signal Process. 49(1): 134-146 (2001) - [j11]Arnaud Doucet, Neil J. Gordon, Vikram Krishnamurthy:
Particle filters for state estimation of jump Markov linear systems. IEEE Trans. Signal Process. 49(3): 613-624 (2001) - [j10]Arnaud Doucet, Christophe Andrieu:
Iterative algorithms for state estimation of jump Markov linear systems. IEEE Trans. Signal Process. 49(6): 1216-1227 (2001) - [c24]Si-Eun Lee, Byoung-Tak Zhang, Arnaud Doucet:
Convergence properties of Bayesian evolutionary algorithms with population size greater than 1. CEC 2001: 326-331 - [c23]Christophe Andrieu, Nando de Freitas, Arnaud Doucet:
Rao-Blackwellised Particle Filtering via Data Augmentation. NIPS 2001: 561-567 - [p2]Arnaud Doucet, Nando de Freitas, Neil J. Gordon:
An Introduction to Sequential Monte Carlo Methods. Sequential Monte Carlo Methods in Practice 2001: 3-14 - [p1]Christophe Andrieu, Arnaud Doucet, Elena Punskaya:
Sequential Monte Carlo Methods for Optimal Filtering. Sequential Monte Carlo Methods in Practice 2001: 79-95 - [e1]Arnaud Doucet, Nando de Freitas, Neil J. Gordon:
Sequential Monte Carlo Methods in Practice. Statistics for Engineering and Information Science, Springer 2001, ISBN 978-1-4419-2887-0 [contents] - 2000
- [j9]João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee, Arnaud Doucet:
Sequential Monte Carlo Methods to Train Neural Network Models. Neural Comput. 12(4): 955-993 (2000) - [j8]Arnaud Doucet, Simon J. Godsill, Christophe Andrieu:
On sequential Monte Carlo sampling methods for Bayesian filtering. Stat. Comput. 10(3): 197-208 (2000) - [j7]Arnaud Doucet, Andrew Logothetis, Vikram Krishnamurthy:
Stochastic sampling algorithms for state estimation of jump Markov linear systems. IEEE Trans. Autom. Control. 45(2): 188-202 (2000) - [j6]Christophe Andrieu, Arnaud Doucet:
Simulated annealing for maximum a Posteriori parameter estimation of hidden Markov models. IEEE Trans. Inf. Theory 46(3): 994-1004 (2000) - [c22]Arnaud Doucet, Neil J. Gordon, Vikram Krishnamurthy:
Sequential simulation-based estimation of jump Markov linear systems. CDC 2000: 1166-1171 - [c21]Arnaud Doucet, Simon J. Godsill, Mike West:
Monte Carlo filtering and smoothing with application to time-varying spectral estimation. ICASSP 2000: 701-704 - [c20]Niclas Bergman, Arnaud Doucet:
Markov chain Monte Carlo data association for target tracking. ICASSP 2000: 705-708 - [c19]Elena Punskaya, Christophe Andrieu, Arnaud Doucet, William J. Fitzgerald:
Particle filters for demodulation of M-ary modulated signals in noisy fading communication channels. ICASSP 2000: 2797-2800 - [c18]A. Ahmed, Christophe Andrieu, Arnaud Doucet, Peter J. W. Rayner:
On-line non-stationary ICA using mixture models. ICASSP 2000: 3148-3151 - [c17]Jaco Vermaak, Christophe Andrieu, Arnaud Doucet:
Particle filtering for non-stationary speech modelling and enhancement. INTERSPEECH 2000: 594-597 - [c16]Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan:
The Unscented Particle Filter. NIPS 2000: 584-590 - [c15]Christophe Andrieu, Nando de Freitas, Arnaud Doucet:
Reversible Jump MCMC Simulated Annealing for Neural Networks. UAI 2000: 11-18 - [c14]Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell:
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. UAI 2000: 176-183
1990 – 1999
- 1999
- [j5]Olivier Cappé, Arnaud Doucet, Marc Lavielle, Eric Moulines:
Simulation-based methods for blind maximum-likelihood filter identification. Signal Process. 73(1-2): 3-25 (1999) - [j4]Christophe Andrieu, Arnaud Doucet:
A Bayesian approach to harmonic retrieval with clipped data. Signal Process. 74(3): 239-252 (1999) - [j3]Christophe Andrieu, Arnaud Doucet:
An improved method for uniform simulation of stable minimum phase real ARMA (p, q) processes. IEEE Signal Process. Lett. 6(6): 142-144 (1999) - [j2]Christophe Andrieu, Arnaud Doucet:
Joint Bayesian model selection and estimation of noisy sinusoids via reversible jump MCMC. IEEE Trans. Signal Process. 47(10): 2667-2676 (1999) - [c13]Christian P. Robert, Arnaud Doucet, Simon J. Godsill:
Marginal MAP estimation using Markov chain Monte Carlo. ICASSP 1999: 1753-1756 - [c12]Arnaud Doucet, Christophe Andrieu:
Iterative algorithms for optimal state estimation of jump Markov linear systems. ICASSP 1999: 2487-2490 - [c11]Mark J. Coates, Arnaud Doucet:
Sequential Bayesian wavelet denoising. ISSPA 1999: 595-598 - [c10]Christophe Andrieu, João F. G. de Freitas, Arnaud Doucet:
Robust Full Bayesian Methods for Neural Networks. NIPS 1999: 379-385 - 1998
- [c9]Christophe Andrieu, Arnaud Doucet:
Efficient stochastic maximum a posteriori estimation for harmonic signals. EUSIPCO 1998: 1-4 - [c8]Arnaud Doucet, Christophe Andrieu:
Robust Bayesian spectral analysis via MCMC sampling. EUSIPCO 1998: 1-4 - [c7]Guillaume Stawinski, Arnaud Doucet, Patrick Duvaut:
Bayesian deconvolution of poissonian point sources. EUSIPCO 1998: 1-4 - [c6]Christophe Andrieu, Arnaud Doucet, Patrick Duvaut:
Joint Bayesian detection and estimation of sinusoids embedded in noise. ICASSP 1998: 2245-2248 - [c5]João F. G. de Freitas, Mahesan Niranjan, Arnaud Doucet, Andrew H. Gee:
Global Optimisation of Neural Network Models via Sequential Sampling. NIPS 1998: 410-416 - 1997
- [j1]Arnaud Doucet, Patrick Duvaut:
Bayesian estimation of state-space models applied to deconvolution of Bernoulli - Gaussian processes. Signal Process. 57(2): 147-161 (1997) - 1996
- [c4]Christophe Andrieu, Patrick Duvaut, Arnaud Doucet:
Bayesian deconvolution of cyclostationary processes based on point processes. EUSIPCO 1996: 1-4 - [c3]Arnaud Doucet, Patrick Duvaut:
Fully Bayesian analysis of Hidden Markov models. EUSIPCO 1996: 1-4 - [c2]Arnaud Doucet, Patrick Duvaut:
Fully Bayesian analysis of conditionally linear Gaussian state space models. ICASSP 1996: 2948-2951 - [c1]Patrick Duvaut, Arnaud Doucet, Christophe Veaux, Patrick Flandrin:
Instantaneous frequency estimation: Bayesian approaches versus reassignment-application to gravitational waves. ICASSP 1996: 2968-2971
Coauthor Index
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