Djolonga, Josip

24 publications

CVPR 2024 End-to-End Spatio-Temporal Action Localisation with Video Transformers Alexey A. Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani, Chen Sun, Mario Lucic, Cordelia Schmid, Anurag Arnab

CVPR 2024 On Scaling up a Multilingual Vision and Language Model 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, Aj 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

ICML 2023 Fast, Differentiable and Sparse Top-K: A Convex Analysis Perspective Michael Eli Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel

NeurIPS 2023 Patch N’ Pack: NaViT, a Vision Transformer for Any Aspect Ratio and Resolution 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 Gritsenko, Mario Lucic, Neil Houlsby

ICML 2023 Scaling Vision Transformers to 22 Billion Parameters 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

ICMLW 2022 SI-Score: An Image Dataset for Fine-Grained Analysis of Robustness to Object Location, Rotation and Size Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai

CVPR 2021 On Robustness and Transferability of Convolutional Neural Networks 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

WACV 2021 Representation Learning from Videos In-the-Wild: An Object-Centric Approach Rob Romijnders, Aravindh Mahendran, Michael Tschannen, Josip Djolonga, Marvin Ritter, Neil Houlsby, Mario Lucic

NeurIPS 2021 Revisiting the Calibration of Modern Neural Networks Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic

ICML 2020 Fast Differentiable Sorting and Ranking Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga

ICLR 2020 On Mutual Information Maximization for Representation Learning Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic

AISTATS 2020 Precision-Recall Curves Using Information Divergence Frontiers Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly

ICLR 2020 You Only Train Once: Loss-Conditional Training of Deep Networks Alexey Dosovitskiy, Josip Djolonga

NeurIPS 2019 Practical and Consistent Estimation of F-Divergences Paul Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O Tolstikhin

NeurIPS 2018 Provable Variational Inference for Constrained Log-Submodular Models Josip Djolonga, Stefanie Jegelka, Andreas Krause

NeurIPS 2017 Differentiable Learning of Submodular Models Josip Djolonga, Andreas Krause

UAI 2017 Improving Optimization-Based Approximate Inference by Clamping Variables Junyao Zhao, Josip Djolonga, Sebastian Tschiatschek, Andreas Krause

NeurIPS 2016 Cooperative Graphical Models Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause

AISTATS 2016 Learning Probabilistic Submodular Diversity Models via Noise Contrastive Estimation Sebastian Tschiatschek, Josip Djolonga, Andreas Krause

NeurIPS 2016 Variational Inference in Mixed Probabilistic Submodular Models Josip Djolonga, Sebastian Tschiatschek, Andreas Krause

ICCV 2015 Higher-Order Inference for Multi-Class Log-Supermodular Models Jian Zhang, Josip Djolonga, Andreas Krause

ICML 2015 Scalable Variational Inference in Log-Supermodular Models Josip Djolonga, Andreas Krause

NeurIPS 2014 From MAP to Marginals: Variational Inference in Bayesian Submodular Models Josip Djolonga, Andreas Krause

NeurIPS 2013 High-Dimensional Gaussian Process Bandits Josip Djolonga, Andreas Krause, Volkan Cevher