Josip Djolonga

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 36

Top Topics

Generative Model

Convolutional Neural Networks

Supervised Learning

Top Venues

Publications

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)
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 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 (2023)
Michael E. Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective. CoRR (2023)
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 (2023)
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)
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 (2023)
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 (2023)
Michael Eli Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective. ICML (2023)
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 (2022)
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)
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)
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 (2021)
Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
Revisiting the Calibration of Modern Neural Networks. CoRR (2021)
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)
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah 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 (2021)
Alexey Dosovitskiy, Josip Djolonga
You Only Train Once: Loss-Conditional Training of Deep Networks. ICLR (2020)
Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga
Fast Differentiable Sorting and Ranking. CoRR (2020)
Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga
Fast Differentiable Sorting and Ranking. ICML (2020)
Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic
On Mutual Information Maximization for Representation Learning. ICLR (2020)
Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly
Precision-Recall Curves Using Information Divergence Frontiers. AISTATS (2020)
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 (2020)
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 (2020)
Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic
Self-Supervised Learning of Video-Induced Visual Invariances. CVPR (2020)
Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin
Practical and Consistent Estimation of f-Divergences. NeurIPS (2019)
Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly
Evaluating Generative Models Using Divergence Frontiers. CoRR (2019)
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 (2019)
Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin
Practical and Consistent Estimation of f-Divergences. CoRR (2019)
Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic
On Mutual Information Maximization for Representation Learning. CoRR (2019)
Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic
Self-Supervised Learning of Video-Induced Visual Invariances. CoRR (2019)
Josip Djolonga, Stefanie Jegelka, Andreas Krause
Provable Variational Inference for Constrained Log-Submodular Models. NeurIPS (2018)
Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
Improving Optimization-Based Approximate Inference by Clamping Variables. UAI (2017)
Josip Djolonga, Andreas Krause
Learning Implicit Generative Models Using Differentiable Graph Tests. CoRR (2017)
Josip Djolonga, Andreas Krause
Differentiable Learning of Submodular Functions. NIPS (2017)
Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause
Cooperative Graphical Models. NIPS (2016)
Sebastian Tschiatschek, Josip Djolonga, Andreas Krause
Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation. AISTATS (2016)
Josip Djolonga, Sebastian Tschiatschek, Andreas Krause
Variational Inference in Mixed Probabilistic Submodular Models. NIPS (2016)
Josip Djolonga, Andreas Krause
Scalable Variational Inference in Log-supermodular Models. CoRR (2015)
Jian Zhang, Josip Djolonga, Andreas Krause
Higher-Order Inference for Multi-class Log-Supermodular Models. ICCV (2015)
Josip Djolonga, Andreas Krause
Scalable Variational Inference in Log-supermodular Models. ICML (2015)
Josip Djolonga, Andreas Krause
From MAP to Marginals: Variational Inference in Bayesian Submodular Models. NIPS (2014)
Josip Djolonga, Andreas Krause, Volkan Cevher
High-Dimensional Gaussian Process Bandits. NIPS (2013)