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ORCIDJosip Djolonga
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2020 – today
- 2024
[c24]Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut:
On Scaling Up a Multilingual Vision and Language Model. CVPR 2024: 14432-14444- [c23]Alexey A. Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid, Anurag Arnab:
End-to-End Spatio-Temporal Action Localisation with Video Transformers. CVPR 2024: 18373-18383 - 2023
- [c22]Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby:
Scaling Vision Transformers to 22 Billion Parameters. ICML 2023: 7480-7512 - [c21]Michael Eli Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel:
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective. ICML 2023: 29919-29936 - [c20]Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim M. Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby:
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. NeurIPS 2023 - [i19]Michael E. Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel:
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective. CoRR abs/2302.01425 (2023) - [i18]Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang
, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby:
Scaling Vision Transformers to 22 Billion Parameters. CoRR abs/2302.05442 (2023) - [i17]Alexey A. Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid, Anurag Arnab:
End-to-End Spatio-Temporal Action Localisation with Video Transformers. CoRR abs/2304.12160 (2023) - [i16]Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut:
PaLI-X: On Scaling up a Multilingual Vision and Language Model. CoRR abs/2305.18565 (2023) - [i15]Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby:
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. CoRR abs/2307.06304 (2023) - 2022
- [i14]Anurag Arnab, Xuehan Xiong, Alexey A. Gritsenko, Rob Romijnders, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid:
Beyond Transfer Learning: Co-finetuning for Action Localisation. CoRR abs/2207.03807 (2022) - 2021
- [c19]Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic:
On Robustness and Transferability of Convolutional Neural Networks. CVPR 2021: 16458-16468 - [c18]Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic:
Revisiting the Calibration of Modern Neural Networks. NeurIPS 2021: 15682-15694 - [c17]Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic:
Representation learning from videos in-the-wild: An object-centric approach. WACV 2021: 177-187 - [i13]Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai:
SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size. CoRR abs/2104.04191 (2021) - [i12]Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Z. Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran:
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR abs/2106.04015 (2021) - [i11]Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic:
Revisiting the Calibration of Modern Neural Networks. CoRR abs/2106.07998 (2021) - 2020
- [c16]Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly:
Precision-Recall Curves Using Information Divergence Frontiers. AISTATS 2020: 2550-2559 - [c15]Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic:
Self-Supervised Learning of Video-Induced Visual Invariances. CVPR 2020: 13803-13812 - [c14]Alexey Dosovitskiy, Josip Djolonga:
You Only Train Once: Loss-Conditional Training of Deep Networks. ICLR 2020 - [c13]Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic:
On Mutual Information Maximization for Representation Learning. ICLR 2020 - [c12]Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga:
Fast Differentiable Sorting and Ranking. ICML 2020: 950-959 - [i10]Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga:
Fast Differentiable Sorting and Ranking. CoRR abs/2002.08871 (2020) - [i9]Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic:
On Robustness and Transferability of Convolutional Neural Networks. CoRR abs/2007.08558 (2020) - [i8]Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic:
Representation learning from videos in-the-wild: An object-centric approach. CoRR abs/2010.02808 (2020)
2010 – 2019
- 2019
- [c11]Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin:
Practical and Consistent Estimation of f-Divergences. NeurIPS 2019: 4072-4082 - [i7]Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly:
Evaluating Generative Models Using Divergence Frontiers. CoRR abs/1905.10768 (2019) - [i6]Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin:
Practical and Consistent Estimation of f-Divergences. CoRR abs/1905.11112 (2019) - [i5]Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic:
On Mutual Information Maximization for Representation Learning. CoRR abs/1907.13625 (2019) - [i4]Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, André Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, Neil Houlsby:
The Visual Task Adaptation Benchmark. CoRR abs/1910.04867 (2019) - [i3]Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic:
Self-Supervised Learning of Video-Induced Visual Invariances. CoRR abs/1912.02783 (2019) - 2018
- [c10]Josip Djolonga, Stefanie Jegelka, Andreas Krause:
Provable Variational Inference for Constrained Log-Submodular Models. NeurIPS 2018: 2702-2712 - 2017
- [c9]Josip Djolonga, Andreas Krause:
Differentiable Learning of Submodular Functions. NIPS 2017: 1013-1023 - [c8]Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause:
Improving Optimization-Based Approximate Inference by Clamping Variables. UAI 2017 - [i2]Josip Djolonga, Andreas Krause:
Learning Implicit Generative Models Using Differentiable Graph Tests. CoRR abs/1709.01006 (2017) - 2016
- [c7]Sebastian Tschiatschek, Josip Djolonga, Andreas Krause:
Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation. AISTATS 2016: 770-779 - [c6]Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause:
Cooperative Graphical Models. NIPS 2016: 262-270 - [c5]Josip Djolonga, Sebastian Tschiatschek, Andreas Krause:
Variational Inference in Mixed Probabilistic Submodular Models. NIPS 2016: 1759-1767 - 2015
- [c4]Jian Zhang, Josip Djolonga, Andreas Krause:
Higher-Order Inference for Multi-class Log-Supermodular Models. ICCV 2015: 1859-1867 - [c3]Josip Djolonga, Andreas Krause:
Scalable Variational Inference in Log-supermodular Models. ICML 2015: 1804-1813 - [i1]Josip Djolonga, Andreas Krause:
Scalable Variational Inference in Log-supermodular Models. CoRR abs/1502.06531 (2015) - 2014
- [c2]Josip Djolonga, Andreas Krause:
From MAP to Marginals: Variational Inference in Bayesian Submodular Models. NIPS 2014: 244-252 - 2013
- [c1]Josip Djolonga, Andreas Krause, Volkan Cevher:
High-Dimensional Gaussian Process Bandits. NIPS 2013: 1025-1033
Coauthor Index
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