Josip Djolonga

43 papers A* 15A 4Journal 19Unranked 5

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	End-to-End Spatio-Temporal Action Localisation with Video Transformers. CVPR Alexey A. Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid, Anurag Arnab
2024	A*	`conf`	On Scaling Up a Multilingual Vision and Language Model. CVPR 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
2023	J	`jnl`	End-to-End Spatio-Temporal Action Localisation with Video Transformers. CoRR Alexey A. Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid, Anurag Arnab
2023	A*	`conf`	Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective. ICML Michael Eli Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel
2023	J	`jnl`	Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective. CoRR Michael E. Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel
2023	J	`jnl`	PaLI-X: On Scaling up a Multilingual Vision and Language Model. CoRR 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
2023	A*	`conf`	Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. NeurIPS 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
2023	J	`jnl`	Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution. CoRR 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
2023	A*	`conf`	Scaling Vision Transformers to 22 Billion Parameters. ICML 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
2023	J	`jnl`	Scaling Vision Transformers to 22 Billion Parameters. CoRR 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
2022	J	`jnl`	Beyond Transfer Learning: Co-finetuning for Action Localisation. CoRR Anurag Arnab, Xuehan Xiong, Alexey A. Gritsenko, Rob Romijnders, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid
2021	A*	`conf`	On Robustness and Transferability of Convolutional Neural Networks. CVPR 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
2021	A	`conf`	Representation learning from videos in-the-wild: An object-centric approach. WACV Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic
2021	A*	`conf`	Revisiting the Calibration of Modern Neural Networks. NeurIPS Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
2021	J	`jnl`	Revisiting the Calibration of Modern Neural Networks. CoRR Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
2021	J	`jnl`	SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size. CoRR Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai
2021	J	`jnl`	Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR 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
2020	A*	`conf`	Fast Differentiable Sorting and Ranking. ICML Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga
2020	J	`jnl`	Fast Differentiable Sorting and Ranking. CoRR Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga
2020	A*	`conf`	On Mutual Information Maximization for Representation Learning. ICLR Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic
2020	J	`jnl`	On Robustness and Transferability of Convolutional Neural Networks. CoRR 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
2020	A	`conf`	Precision-Recall Curves Using Information Divergence Frontiers. AISTATS Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly
2020	J	`jnl`	Representation learning from videos in-the-wild: An object-centric approach. CoRR Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic
2020	A*	`conf`	Self-Supervised Learning of Video-Induced Visual Invariances. CVPR Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic
2020	A*	`conf`	You Only Train Once: Loss-Conditional Training of Deep Networks. ICLR Alexey Dosovitskiy, Josip Djolonga
2019	J	`jnl`	Evaluating Generative Models Using Divergence Frontiers. CoRR Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly
2019	J	`jnl`	On Mutual Information Maximization for Representation Learning. CoRR Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic
2019	A*	`conf`	Practical and Consistent Estimation of f-Divergences. NeurIPS Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin
2019	J	`jnl`	Practical and Consistent Estimation of f-Divergences. CoRR Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin
2019	J	`jnl`	Self-Supervised Learning of Video-Induced Visual Invariances. CoRR Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic
2019	J	`jnl`	The Visual Task Adaptation Benchmark. CoRR 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
2018	A*	`conf`	Provable Variational Inference for Constrained Log-Submodular Models. NeurIPS Josip Djolonga, Stefanie Jegelka, Andreas Krause
2017	—	`conf`	Differentiable Learning of Submodular Functions. NIPS Josip Djolonga, Andreas Krause
2017	A	`conf`	Improving Optimization-Based Approximate Inference by Clamping Variables. UAI Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
2017	J	`jnl`	Learning Implicit Generative Models Using Differentiable Graph Tests. CoRR Josip Djolonga, Andreas Krause
2016	—	`conf`	Cooperative Graphical Models. NIPS Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause
2016	A	`conf`	Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation. AISTATS Sebastian Tschiatschek, Josip Djolonga, Andreas Krause
2016	—	`conf`	Variational Inference in Mixed Probabilistic Submodular Models. NIPS Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
2015	A*	`conf`	Higher-Order Inference for Multi-class Log-Supermodular Models. ICCV Jian Zhang, Josip Djolonga, Andreas Krause
2015	A*	`conf`	Scalable Variational Inference in Log-supermodular Models. ICML Josip Djolonga, Andreas Krause
2015	J	`jnl`	Scalable Variational Inference in Log-supermodular Models. CoRR Josip Djolonga, Andreas Krause
2014	—	`conf`	From MAP to Marginals: Variational Inference in Bayesian Submodular Models. NIPS Josip Djolonga, Andreas Krause
2013	—	`conf`	High-Dimensional Gaussian Process Bandits. NIPS Josip Djolonga, Andreas Krause, Volkan Cevher