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2020 – today
- 2023
[c72]Aliaksandra Shysheya, John Bronskill, Massimiliano Patacchiola, Sebastian Nowozin, Richard E. Turner:
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification. ICLR 2023- [c71]Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noé, Ryota Tomioka:
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics. NeurIPS 2023 - [c70]Patrick Anderson
, Erika Blancada Aranas, Youssef Assaf, Raphael Behrendt, Richard Black, Marco Caballero, Pashmina Cameron, Burcu Canakci, Thales De Carvalho, Andromachi Chatzieleftheriou, Rebekah Storan Clarke, James Clegg, Daniel Cletheroe, Bridgette Cooper, Tim Deegan, Austin Donnelly, Rokas Drevinskas, Alexander L. Gaunt, Christos Gkantsidis, Ariel Gomez Diaz, István Haller, Freddie Hong, Teodora Ilieva, Shashidhar Joshi, Russell Joyce, Mint Kunkel, David Lara, Sergey Legtchenko, Fanglin Linda Liu, Bruno Magalhães, Alana Marzoev, Marvin McNett, Jayashree Mohan, Michael Myrah, Trong Nguyen, Sebastian Nowozin, Aaron Ogus, Hiske Overweg, Antony I. T. Rowstron, Maneesh Sah, Masaaki Sakakura, Peter Scholtz, Nina Schreiner, Omer Sella, Adam Smith, Ioan A. Stefanovici, David Sweeney, Benn Thomsen, Govert Verkes, Phil Wainman, Jonathan Westcott, Luke Weston, Charles Whittaker, Pablo Wilke Berenguer, Hugh Williams, Thomas Winkler, Stefan Winzeck:
Project Silica: Towards Sustainable Cloud Archival Storage in Glass. SOSP 2023: 166-181 - [i42]Joowon Lim, Jannes Gladrow, Douglas Kelly, Greg O'Shea, Govert Verkes, Ioan A. Stefanovici, Sebastian Nowozin, Benn Thomsen:
High-bandwidth Close-Range Information Transport through Light Pipes. CoRR abs/2301.06496 (2023) - [i41]Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noé, Ryota Tomioka:
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics. CoRR abs/2302.01170 (2023) - 2022
- [c69]Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E. Turner:
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. NeurIPS 2022 - [i40]Aliaksandra Shysheya, John Bronskill, Massimiliano Patacchiola, Sebastian Nowozin, Richard E. Turner:
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification. CoRR abs/2206.08671 (2022) - [i39]Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E. Turner:
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. CoRR abs/2206.09843 (2022) - 2021
- [c68]Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann:
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect. NeurIPS 2021: 12738-12748 - [c67]Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann:
Precise characterization of the prior predictive distribution of deep ReLU networks. NeurIPS 2021: 20851-20862 - [c66]John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard E. Turner:
Memory Efficient Meta-Learning with Large Images. NeurIPS 2021: 24327-24339 - [i38]Lorenzo Noci, Kevin Roth, Gregor Bachmann, Sebastian Nowozin, Thomas Hofmann:
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect. CoRR abs/2106.06596 (2021) - [i37]Lorenzo Noci, Gregor Bachmann, Kevin Roth, Sebastian Nowozin, Thomas Hofmann:
Precise characterization of the prior predictive distribution of deep ReLU networks. CoRR abs/2106.06615 (2021) - [i36]John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard E. Turner:
Memory Efficient Meta-Learning with Large Images. CoRR abs/2107.01105 (2021) - 2020
- [c65]Jan Stuehmer, Richard E. Turner, Sebastian Nowozin:
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations. AISTATS 2020: 1200-1210 - [c64]John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner:
TaskNorm: Rethinking Batch Normalization for Meta-Learning. ICML 2020: 1153-1164 - [c63]Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. ICML 2020: 9289-9299 - [c62]Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML 2020: 10248-10259 - [i35]Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton:
Hydra: Preserving Ensemble Diversity for Model Distillation. CoRR abs/2001.04694 (2020) - [i34]Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR abs/2002.02405 (2020) - [i33]Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin:
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. CoRR abs/2002.02655 (2020) - [i32]John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner:
TaskNorm: Rethinking Batch Normalization for Meta-Learning. CoRR abs/2003.03284 (2020)
2010 – 2019
- 2019
- [c61]Lars M. Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, Andreas Geiger:
Occupancy Networks: Learning 3D Reconstruction in Function Space. CVPR 2019: 4460-4470 - [c60]Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner:
Meta-Learning Probabilistic Inference for Prediction. ICLR (Poster) 2019 - [c59]Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt:
Deterministic Variational Inference for Robust Bayesian Neural Networks. ICLR 2019 - [c58]Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang:
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. ICML 2019: 4234-4243 - [c57]James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner:
Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes. NeurIPS 2019: 7957-7968 - [c56]Jasper Snoek, Yaniv Ovadia, Emily Fertig, Balaji Lakshminarayanan, Sebastian Nowozin, D. Sculley, Joshua V. Dillon, Jie Ren, Zachary Nado:
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift. NeurIPS 2019: 13969-13980 - [c55]Wenbo Gong, Sebastian Tschiatschek, Sebastian Nowozin, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang:
Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model. NeurIPS 2019: 14791-14802 - [i31]Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, David Sculley, Sebastian Nowozin, Joshua V. Dillon, Balaji Lakshminarayanan, Jasper Snoek:
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift. CoRR abs/1906.02530 (2019) - [i30]James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner:
Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes. CoRR abs/1906.07697 (2019) - [i29]Wenbo Gong, Sebastian Tschiatschek, Richard E. Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang:
Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model. CoRR abs/1908.04537 (2019) - [i28]Jan Stühmer, Richard E. Turner, Sebastian Nowozin:
Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations. CoRR abs/1909.05063 (2019) - 2018
- [c54]Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin:
Multi-Level Variational Autoencoder: Learning Disentangled Representations From Grouped Observations. AAAI 2018: 2095-2102 - [c53]Sergey Prokudin, Peter V. Gehler, Sebastian Nowozin:
Deep Directional Statistics: Pose Estimation with Uncertainty Quantification. ECCV (9) 2018: 542-559 - [c52]Daniel Coelho de Castro, Sebastian Nowozin:
From Face Recognition to Models of Identity: A Bayesian Approach to Learning About Unknown Identities from Unsupervised Data. ECCV (2) 2018: 764-780 - [c51]Patrick Anderson, Richard Black, Ausra Cerkauskaite, Andromachi Chatzieleftheriou, James Clegg, Chris Dainty, Raluca Diaconu, Rokas Drevinskas, Austin Donnelly, Alexander L. Gaunt, Andreas Georgiou, Ariel Gomez Diaz, Peter G. Kazansky, David Lara, Sergey Legtchenko, Sebastian Nowozin, Aaron Ogus, Douglas Phillips, Antony I. T. Rowstron, Masaaki Sakakura, Ioan A. Stefanovici, Benn Thomsen, Lei Wang, Hugh Williams, Mengyang Yang:
Glass: A New Media for a New Era? HotStorage 2018 - [c50]Sebastian Nowozin:
Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational Inference. ICLR (Poster) 2018 - [c49]Yang Song, Taesup Kim, Sebastian Nowozin, Stefano Ermon, Nate Kushman:
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples. ICLR (Poster) 2018 - [c48]Lars M. Mescheder, Andreas Geiger, Sebastian Nowozin:
Which Training Methods for GANs do actually Converge? ICML 2018: 3478-3487 - [i27]Sergey Prokudin, Peter V. Gehler, Sebastian Nowozin:
Deep Directional Statistics: Pose Estimation with Uncertainty Quantification. CoRR abs/1805.03430 (2018) - [i26]Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann:
Adversarially Robust Training through Structured Gradient Regularization. CoRR abs/1805.08736 (2018) - [i25]Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner:
Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning. CoRR abs/1805.09921 (2018) - [i24]Daniel Coelho de Castro, Sebastian Nowozin:
From Face Recognition to Models of Identity: A Bayesian Approach to Learning about Unknown Identities from Unsupervised Data. CoRR abs/1807.07872 (2018) - [i23]Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, Cheng Zhang:
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE. CoRR abs/1809.11142 (2018) - [i22]Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt:
Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks. CoRR abs/1810.03958 (2018) - [i21]Daniel Coelho de Castro, Sebastian Nowozin:
Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model. CoRR abs/1811.07753 (2018) - [i20]Lars M. Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, Andreas Geiger:
Occupancy Networks: Learning 3D Reconstruction in Function Space. CoRR abs/1812.03828 (2018) - 2017
- [j10]Amit Adam, Christoph Dann, Omer Yair, Shai Mazor, Sebastian Nowozin:
Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo. IEEE Trans. Pattern Anal. Mach. Intell. 39(5): 851-864 (2017) - [c47]Michael Schober, Amit Adam, Omer Yair, Shai Mazor, Sebastian Nowozin:
Dynamic Time-of-Flight. CVPR 2017: 170-179 - [c46]Eric Brachmann, Alexander Krull, Sebastian Nowozin, Jamie Shotton, Frank Michel, Stefan Gumhold, Carsten Rother:
DSAC - Differentiable RANSAC for Camera Localization. CVPR 2017: 2492-2500 - [c45]Alexander Krull, Eric Brachmann, Sebastian Nowozin, Frank Michel, Jamie Shotton, Carsten Rother:
PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning. CVPR 2017: 2566-2574 - [c44]Sergey Prokudin, Daniel Kappler, Sebastian Nowozin, Peter V. Gehler:
Learning to Filter Object Detections. GCPR 2017: 52-62 - [c43]Matej Balog, Alexander L. Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow:
DeepCoder: Learning to Write Programs. ICLR (Poster) 2017 - [c42]Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger:
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks. ICML 2017: 2391-2400 - [c41]Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger:
The Numerics of GANs. NIPS 2017: 1825-1835 - [c40]Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann:
Stabilizing Training of Generative Adversarial Networks through Regularization. NIPS 2017: 2018-2028 - [i19]Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger:
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks. CoRR abs/1701.04722 (2017) - [i18]Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin:
Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations. CoRR abs/1705.08841 (2017) - [i17]Kevin Roth, Aurélien Lucchi, Sebastian Nowozin, Thomas Hofmann:
Stabilizing Training of Generative Adversarial Networks through Regularization. CoRR abs/1705.09367 (2017) - [i16]Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger:
The Numerics of GANs. CoRR abs/1705.10461 (2017) - [i15]Vitaly Kurin, Sebastian Nowozin, Katja Hofmann, Lucas Beyer, Bastian Leibe:
The Atari Grand Challenge Dataset. CoRR abs/1705.10998 (2017) - [i14]Yang Song, Taesup Kim, Sebastian Nowozin, Stefano Ermon, Nate Kushman:
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples. CoRR abs/1710.10766 (2017) - [i13]Sergey Tulyakov, Andrew W. Fitzgibbon, Sebastian Nowozin:
Hybrid VAE: Improving Deep Generative Models using Partial Observations. CoRR abs/1711.11566 (2017) - 2016
- [j9]Uwe Schmidt, Jeremy Jancsary, Sebastian Nowozin, Stefan Roth, Carsten Rother:
Cascades of Regression Tree Fields for Image Restoration. IEEE Trans. Pattern Anal. Mach. Intell. 38(4): 677-689 (2016) - [c39]Christian Daniel, Jonathan Taylor, Sebastian Nowozin:
Learning Step Size Controllers for Robust Neural Network Training. AAAI 2016: 1519-1525 - [c38]Sebastian Nowozin, Botond Cseke, Ryota Tomioka:
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. NIPS 2016: 271-279 - [c37]Diane Bouchacourt, Pawan Kumar Mudigonda, Sebastian Nowozin:
DISCO Nets : DISsimilarity COefficients Networks. NIPS 2016: 352-360 - [c36]Olga Ohrimenko, Felix Schuster, Cédric Fournet, Aastha Mehta, Sebastian Nowozin, Kapil Vaswani, Manuel Costa:
Oblivious Multi-Party Machine Learning on Trusted Processors. USENIX Security Symposium 2016: 619-636 - [i12]Sebastian Nowozin, Botond Cseke, Ryota Tomioka:
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. CoRR abs/1606.00709 (2016) - [i11]Diane Bouchacourt, M. Pawan Kumar, Sebastian Nowozin:
DISCO Nets: DISsimilarity COefficient Networks. CoRR abs/1606.02556 (2016) - [i10]Matej Balog, Alexander L. Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow:
DeepCoder: Learning to Write Programs. CoRR abs/1611.01989 (2016) - [i9]Eric Brachmann, Alexander Krull, Sebastian Nowozin, Jamie Shotton, Frank Michel, Stefan Gumhold, Carsten Rother:
DSAC - Differentiable RANSAC for Camera Localization. CoRR abs/1611.05705 (2016) - [i8]Lars M. Mescheder, Sebastian Nowozin, Andreas Geiger:
Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring. CoRR abs/1611.06684 (2016) - [i7]Christoph Dann, Katja Hofmann, Sebastian Nowozin:
Memory Lens: How Much Memory Does an Agent Use? CoRR abs/1611.06928 (2016) - [i6]Alexander Krull, Eric Brachmann, Sebastian Nowozin, Frank Michel, Jamie Shotton, Carsten Rother:
PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning. CoRR abs/1612.03779 (2016) - 2015
- [j8]Varun Jampani, Sebastian Nowozin, Matthew Loper, Peter V. Gehler:
The informed sampler: A discriminative approach to Bayesian inference in generative computer vision models. Comput. Vis. Image Underst. 136: 32-44 (2015) - [j7]Jörg H. Kappes, Björn Andres, Fred A. Hamprecht, Christoph Schnörr, Sebastian Nowozin, Dhruv Batra, Sungwoong Kim, Bernhard X. Kausler, Thorben Kröger, Jan Lellmann, Nikos Komodakis, Bogdan Savchynskyy, Carsten Rother:
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. Int. J. Comput. Vis. 115(2): 155-184 (2015) - [c35]Diane Bouchacourt, Sebastian Nowozin, M. Pawan Kumar:
Entropy-Based Latent Structured Output Prediction. ICCV 2015: 2920-2928 - [c34]Jan Stühmer, Sebastian Nowozin, Andrew W. Fitzgibbon, Richard Szeliski, Travis Perry, Sunil Acharya, Daniel Cremers, Jamie Shotton:
Model-Based Tracking at 300Hz Using Raw Time-of-Flight Observations. ICCV 2015: 3577-3585 - [c33]Kevin Schelten, Sebastian Nowozin, Jeremy Jancsary, Carsten Rother, Stefan Roth:
Interleaved Regression Tree Field Cascades for Blind Image Deconvolution. WACV 2015: 494-501 - [i5]Amit Adam, Christoph Dann, Omer Yair, Shai Mazor, Sebastian Nowozin:
Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedo. CoRR abs/1507.06173 (2015) - 2014
- [j6]Sungwoong Kim, Chang Dong Yoo, Sebastian Nowozin, Pushmeet Kohli:
Image Segmentation UsingHigher-Order Correlation Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 36(9): 1761-1774 (2014) - [j5]Daniel Khashabi, Sebastian Nowozin, Jeremy Jancsary, Andrew W. Fitzgibbon:
Joint Demosaicing and Denoising via Learned Nonparametric Random Fields. IEEE Trans. Image Process. 23(12): 4968-4981 (2014) - [c32]Sebastian Nowozin:
Optimal Decisions from Probabilistic Models: The Intersection-over-Union Case. CVPR 2014: 548-555 - [c31]Andreas M. Lehrmann, Peter V. Gehler, Sebastian Nowozin:
Efficient Nonlinear Markov Models for Human Motion. CVPR 2014: 1314-1321 - [c30]Yuting Wu, Daniel J. Holland, Mick D. Mantle, Andrew Gordon Wilson, Sebastian Nowozin, Andrew Blake, Lynn F. Gladden:
A Bayesian method to quantifying chemical composition using NMR: Application to porous media systems. EUSIPCO 2014: 2515-2519 - [c29]Sébastien Bratières, Novi Quadrianto, Sebastian Nowozin, Zoubin Ghahramani:
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications. ICML 2014: 334-342 - [i4]Varun Jampani, Sebastian Nowozin, Matthew Loper, Peter V. Gehler:
The Informed Sampler: A Discriminative Approach to Bayesian Inference in Generative Computer Vision Models. CoRR abs/1402.0859 (2014) - [i3]Jörg H. Kappes, Björn Andres, Fred A. Hamprecht, Christoph Schnörr, Sebastian Nowozin, Dhruv Batra, Sungwoong Kim, Bernhard X. Kausler, Thorben Kröger, Jan Lellmann, Nikos Komodakis, Bogdan Savchynskyy, Carsten Rother:
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. CoRR abs/1404.0533 (2014) - [i2]Uwe Schmidt, Jeremy Jancsary, Sebastian Nowozin, Stefan Roth, Carsten Rother:
Cascades of Regression Tree Fields for Image Restoration. CoRR abs/1404.2086 (2014) - 2013
- [j4]Sungwoong Kim, Sebastian Nowozin, Pushmeet Kohli, Chang D. Yoo:
Task-Specific Image Partitioning. IEEE Trans. Image Process. 22(2): 488-500 (2013) - [c28]Po-Ling Loh, Sebastian Nowozin:
Faster Hoeffding Racing: Bernstein Races via Jackknife Estimates. ALT 2013: 203-217 - [c27]Uwe Schmidt, Carsten Rother, Sebastian Nowozin, Jeremy Jancsary, Stefan Roth:
Discriminative Non-blind Deblurring. CVPR 2013: 604-611 - [c26]Jörg H. Kappes, Björn Andres, Fred A. Hamprecht, Christoph Schnörr, Sebastian Nowozin, Dhruv Batra, Sungwoong Kim, Bernhard X. Kausler, Jan Lellmann, Nikos Komodakis, Carsten Rother:
A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems. CVPR 2013: 1328-1335 - [c25]Andreas M. Lehrmann, Peter V. Gehler, Sebastian Nowozin:
A Non-parametric Bayesian Network Prior of Human Pose. ICCV 2013: 1281-1288 - [c24]Jeremy Jancsary, Sebastian Nowozin, Carsten Rother:
Learning Convex QP Relaxations for Structured Prediction. ICML (3) 2013: 915-923 - [c23]Jamie Shotton, Toby Sharp, Pushmeet Kohli, Sebastian Nowozin, John M. Winn, Antonio Criminisi:
Decision Jungles: Compact and Rich Models for Classification. NIPS 2013: 234-242 - 2012
- [c22]Simon Fothergill, Helena M. Mentis, Pushmeet Kohli, Sebastian Nowozin:
Instructing people for training gestural interactive systems. CHI 2012: 1737-1746 - [c21]Jeremy Jancsary, Sebastian Nowozin, Toby Sharp, Carsten Rother:
Regression Tree Fields - An efficient, non-parametric approach to image labeling problems. CVPR 2012: 2376-2383 - [c20]Andreas C. Müller, Sebastian Nowozin, Christoph H. Lampert:
Information Theoretic Clustering Using Minimum Spanning Trees. DAGM/OAGM Symposium 2012: 205-215 - [c19]Christoph Dann, Peter V. Gehler, Stefan Roth, Sebastian Nowozin:
Pottics - The Potts Topic Model for Semantic Image Segmentation. DAGM/OAGM Symposium 2012: 397-407 - [c18]Jeremy Jancsary, Sebastian Nowozin, Carsten Rother:
Loss-Specific Training of Non-Parametric Image Restoration Models: A New State of the Art. ECCV (7) 2012: 112-125 - [c17]Sebastian Nowozin:
Improved Information Gain Estimates for Decision Tree Induction. ICML 2012 - [i1]Sebastian Nowozin:
Improved Information Gain Estimates for Decision Tree Induction. CoRR abs/1206.4620 (2012) - 2011
- [j3]Sebastian Nowozin, Christoph H. Lampert:
Structured Learning and Prediction in Computer Vision. Found. Trends Comput. Graph. Vis. 6(3-4): 185-365 (2011) - [c16]Taesup Kim, Sebastian Nowozin, Pushmeet Kohli, Chang D. Yoo:
Variable grouping for energy minimization. CVPR 2011: 1913-1920 - [c15]Patrick Pletscher, Sebastian Nowozin, Pushmeet Kohli, Carsten Rother:
Putting MAP Back on the Map. DAGM-Symposium 2011: 111-121 - [c14]Sebastian Nowozin, Carsten Rother, Shai Bagon, Toby Sharp, Bangpeng Yao, Pushmeet Kohli:
Decision tree fields. ICCV 2011: 1668-1675 - [c13]Sungwoong Kim, Sebastian Nowozin, Pushmeet Kohli, Chang Dong Yoo:
Higher-Order Correlation Clustering for Image Segmentation. NIPS 2011: 1530-1538 - [c12]Dhruv Batra, Sebastian Nowozin, Pushmeet Kohli:
Tighter Relaxations for MAP-MRF Inference: A Local Primal-Dual Gap based Separation Algorithm. AISTATS 2011: 146-154 - 2010
- [j2]Sebastian Nowozin, Christoph H. Lampert:
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness. SIAM J. Imaging Sci. 3(4): 1048-1074 (2010) - [c11]Sebastian Nowozin, Peter V. Gehler, Christoph H. Lampert:
On Parameter Learning in CRF-Based Approaches to Object Class Image Segmentation. ECCV (6) 2010: 98-111
2000 – 2009
- 2009
- [b1]Sebastian Nowozin:
Learning with structured data: applications to computer vision. Berlin Institute of Technology, 2009 - [j1]Hiroto Saigo, Sebastian Nowozin, Tadashi Kadowaki, Taku Kudo, Koji Tsuda:
gBoost: a mathematical programming approach to graph classification and regression. Mach. Learn. 75(1): 69-89 (2009) - [c10]Paramveer S. Dhillon, Sebastian Nowozin, Christoph H. Lampert:
Combining appearance and motion for human action classification in videos. CVPR Workshops 2009: 22-29 - [c9]Sebastian Nowozin, Christoph H. Lampert:
Global connectivity potentials for random field models. CVPR 2009: 818-825 - [c8]Peter V. Gehler, Sebastian Nowozin:
Let the kernel figure it out; Principled learning of pre-processing for kernel classifiers. CVPR 2009: 2836-2843 - [c7]Peter V. Gehler, Sebastian Nowozin:
On feature combination for multiclass object classification. ICCV 2009: 221-228 - [c6]Sebastian Nowozin, Stefanie Jegelka:
Solution stability in linear programming relaxations: graph partitioning and unsupervised learning. ICML 2009: 769-776 - 2008
- [c5]Sebastian Nowozin, Koji Tsuda:
Frequent Subgraph Retrieval in Geometric Graph Databases. ICDM 2008: 953-958 - [c4]Sebastian Nowozin, Gökhan H. Bakir:
A decoupled approach to exemplar-based unsupervised learning. ICML 2008: 704-711 - 2007
- [c3]Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku Kudo, Gökhan H. Bakir:
Weighted Substructure Mining for Image Analysis. CVPR 2007 - [c2]Sebastian Nowozin, Gökhan H. Bakir, Koji Tsuda:
Discriminative Subsequence Mining for Action Classification. ICCV 2007: 1-8 - [c1]Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku Kudo, Gökhan H. Bakir:
Weighted Substructure Mining for Image Analysis. MLG 2007
Coauthor Index
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Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-04 00:23 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
