Lucic, Mario

42 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

ICCV 2023 Audiovisual Masked Autoencoders Mariana-Iuliana Georgescu, Eduardo Fonseca, Radu Tudor Ionescu, Mario Lucic, Cordelia Schmid, Anurag Arnab

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

TMLR 2023 PolyViT: Co-Training Vision Transformers on Images, Videos and Audio Valerii Likhosherstov, Anurag Arnab, Krzysztof Marcin Choromanski, Mario Lucic, Yi Tay, Mostafa Dehghani

CVPR 2023 RUST: Latent Neural Scene Representations from Unposed Imagery Mehdi S. M. Sajjadi, Aravindh Mahendran, Thomas Kipf, Etienne Pot, Daniel Duckworth, Mario Lučić, Klaus Greff

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

ICCV 2023 Video OWL-ViT: Temporally-Consistent Open-World Localization in Video Georg Heigold, Matthias Minderer, Alexey Gritsenko, Alex Bewley, Daniel Keysers, Mario Lučić, Fisher Yu, Thomas Kipf

NeurIPS 2022 Object Scene Representation Transformer Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetic, Mario Lucic, Leonidas Guibas, Klaus Greff, Thomas Kipf

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 2022 Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations Mehdi S. M. Sajjadi, Henning Meyer, Etienne Pot, Urs Bergmann, Klaus Greff, Noha Radwan, Suhani Vora, Mario Lučić, Daniel Duckworth, Alexey Dosovitskiy, Jakob Uszkoreit, Thomas Funkhouser, Andrea Tagliasacchi

JMLR 2022 Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander D'Amour, Katherine Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yian Ma, Cory McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley

NeurIPS 2022 VCT: A Video Compression Transformer Fabian Mentzer, George D Toderici, David Minnen, Sergi Caelles, Sung Jin Hwang, Mario Lucic, Eirikur Agustsson

CVPR 2022 Which Model to Transfer? Finding the Needle in the Growing Haystack Cedric Renggli, André Susano Pinto, Luka Rimanic, Joan Puigcerver, Carlos Riquelme, Ce Zhang, Mario Lučić

NeurIPS 2021 A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models Ibrahim M Alabdulmohsin, Mario Lucic

NeurIPS 2021 MLP-Mixer: An All-MLP Architecture for Vision Ilya O Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy

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

ICCV 2021 ViViT: A Video Vision Transformer Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lučić, Cordelia Schmid

AAAI 2020 A Commentary on the Unsupervised Learning of Disentangled Representations Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem

JMLR 2020 A Sober Look at the Unsupervised Learning of Disentangled Representations and Their Evaluation Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Raetsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem

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

ICML 2019 A Large-Scale Study on Regularization and Normalization in GANs Karol Kurach, Mario Lučić, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly

ICML 2019 Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Raetsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem

ICLR 2019 On Self Modulation for Generative Adversarial Networks Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly

NeurIPS 2018 Are GANs Created Equal? a Large-Scale Study Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet

NeurIPS 2018 Assessing Generative Models via Precision and Recall Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, Sylvain Gelly

NeurIPS 2018 Deep Generative Models for Distribution-Preserving Lossy Compression Michael Tschannen, Eirikur Agustsson, Mario Lucic

AISTATS 2018 One-Shot Coresets: The Case of K-Clustering Olivier Bachem, Mario Lucic, Silvio Lattanzi

ICML 2017 Distributed and Provably Good Seedings for K-Means in Constant Rounds Olivier Bachem, Mario Lucic, Andreas Krause

NeurIPS 2017 Stochastic Submodular Maximization: The Case of Coverage Functions Mohammad Karimi, Mario Lucic, Hamed Hassani, Andreas Krause

ICML 2017 Uniform Deviation Bounds for K-Means Clustering Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause

AAAI 2016 Approximate K-Means++ in Sublinear Time Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause

NeurIPS 2016 Fast and Provably Good Seedings for K-Means Olivier Bachem, Mario Lucic, Hamed Hassani, Andreas Krause

ICML 2016 Horizontally Scalable Submodular Maximization Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam, Andreas Krause

IJCAI 2016 Linear-Time Outlier Detection via Sensitivity Mario Lucic, Olivier Bachem, Andreas Krause

AISTATS 2016 Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures Mario Lucic, Olivier Bachem, Andreas Krause

ICML 2015 Coresets for Nonparametric Estimation - The Case of DP-Means Olivier Bachem, Mario Lucic, Andreas Krause

AISTATS 2015 Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi, Andreas Krause

NeurIPS 2014 Fast and Robust Least Squares Estimation in Corrupted Linear Models Brian McWilliams, Gabriel Krummenacher, Mario Lucic, Joachim M Buhmann