Michael Tschannen

95 papers A* 25A 2B 2Journal 53Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Jet: A Modern Transformer-Based Normalizing Flow. Trans. Mach. Learn. Res. Alexander Kolesnikov, André Susano Pinto, Michael Tschannen
2025	A*	`conf`	JetFormer: An autoregressive generative model of raw images and text. ICLR Michael Tschannen, André Susano Pinto, Alexander Kolesnikov
2025	J	`jnl`	Quantization-Free Autoregressive Action Transformer. CoRR Ziyad Sheebaelhamd, Michael Tschannen, Michael Muehlebach, Claire Vernade
2025	J	`jnl`	SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features. CoRR Michael Tschannen, Alexey A. Gritsenko, Xiao Wang, Muhammad Ferjad Naeem, Ibrahim Alabdulmohsin, Nikhil Parthasarathy, Talfan Evans, Lucas Beyer, Ye Xia, Basil Mustafa, Olivier J. Hénaff, Jeremiah Harmsen, Andreas Steiner, Xiaohua Zhai
2024	A*	`conf`	Finite Scalar Quantization: VQ-VAE Made Simple. ICLR Fabian Mentzer, David Minnen, Eirikur Agustsson, Michael Tschannen
2024	—	`conf`	GIVT: Generative Infinite-Vocabulary Transformers. ECCV (57) Michael Tschannen, Cian Eastwood, Fabian Mentzer
2024	J	`jnl`	Jet: A Modern Transformer-Based Normalizing Flow. CoRR Alexander Kolesnikov, André Susano Pinto, Michael Tschannen
2024	J	`jnl`	JetFormer: An Autoregressive Generative Model of Raw Images and Text. CoRR Michael Tschannen, André Susano Pinto, Alexander Kolesnikov
2024	A*	`conf`	LocCa: Visual Pretraining with Location-aware Captioners. NeurIPS Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic, Ibrahim M. Alabdulmohsin, Xiao Wang, André Susano Pinto, Andreas Steiner, Lucas Beyer, Xiaohua Zhai
2024	J	`jnl`	LocCa: Visual Pretraining with Location-aware Captioners. CoRR Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic, Ibrahim Alabdulmohsin, Xiao Wang, André Susano Pinto, Andreas Steiner, Lucas Beyer, Xiaohua Zhai
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
2024	J	`jnl`	PaliGemma 2: A Family of Versatile VLMs for Transfer. CoRR Andreas Steiner, André Susano Pinto, Michael Tschannen, Daniel Keysers, Xiao Wang, Yonatan Bitton, Alexey A. Gritsenko, Matthias Minderer, Anthony Sherbondy, Shangbang Long, Siyang Qin, R. Reeve Ingle, Emanuele Bugliarello, Sahar Kazemzadeh, Thomas Mesnard, Ibrahim Alabdulmohsin, Lucas Beyer, Xiaohua Zhai
2024	J	`jnl`	PaliGemma: A versatile 3B VLM for transfer. CoRR Lucas Beyer, Andreas Steiner, André Susano Pinto, Alexander Kolesnikov, Xiao Wang, Daniel Salz, Maxim Neumann, Ibrahim Alabdulmohsin, Michael Tschannen, Emanuele Bugliarello, Thomas Unterthiner, Daniel Keysers, Skanda Koppula, Fangyu Liu, Adam Grycner, Alexey A. Gritsenko, Neil Houlsby, Manoj Kumar, Keran Rong, Julian Eisenschlos, Rishabh Kabra, Matthias Bauer, Matko Bosnjak, Xi Chen, Matthias Minderer, Paul Voigtlaender, Ioana Bica, Ivana Balazevic, Joan Puigcerver, Pinelopi Papalampidi, Olivier J. Hénaff, Xi Xiong, Radu Soricut, Jeremiah Harmsen, Xiaohua Zhai
2024	J	`jnl`	Towards Truly Zero-shot Compositional Visual Reasoning with LLMs as Programmers. CoRR Aleksandar Stanic, Sergi Caelles, Michael Tschannen
2024	J	`jnl`	Towards Truly Zero-shot Compositional Visual Reasoning with LLMs as Programmers. Trans. Mach. Learn. Res. Aleksandar Stanic, Sergi Caelles, Michael Tschannen
2023	A*	`conf`	CLIPPO: Image-and-Language Understanding from Pixels Only. CVPR Michael Tschannen, Basil Mustafa, Neil Houlsby
2023	J	`jnl`	Finite Scalar Quantization: VQ-VAE Made Simple. CoRR Fabian Mentzer, David Minnen, Eirikur Agustsson, Michael Tschannen
2023	A*	`conf`	FlexiViT: One Model for All Patch Sizes. CVPR Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
2023	J	`jnl`	GIVT: Generative Infinite-Vocabulary Transformers. CoRR Michael Tschannen, Cian Eastwood, Fabian Mentzer
2023	A*	`conf`	Image Captioners Are Scalable Vision Learners Too. NeurIPS Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer
2023	J	`jnl`	Image Captioners Are Scalable Vision Learners Too. CoRR Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer
2023	A*	`conf`	M2T: Masking Transformers Twice for Faster Decoding. ICCV Fabian Mentzer, Eirikur Agustsson, Michael Tschannen
2023	J	`jnl`	M2T: Masking Transformers Twice for Faster Decoding. CoRR Fabian Mentzer, Eirikur Agustsson, Michael Tschannen
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`	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`	FlexiViT: One Model for All Patch Sizes. CoRR Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
2022	J	`jnl`	Image-and-Language Understanding from Pixels Only. CoRR Michael Tschannen, Basil Mustafa, Neil Houlsby
2022	—	`conf`	Neural Face Video Compression using Multiple Views. CVPR Workshops Anna Volokitin, Stefan Brugger, Ali Benlalah, Sebastian Martin, Brian Amberg, Michael Tschannen
2022	J	`jnl`	Neural Face Video Compression using Multiple Views. CoRR Anna Volokitin, Stefan Brugger, Ali Benlalah, Sebastian Martin, Brian Amberg, Michael Tschannen
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
2020	A*	`conf`	Automatic Shortcut Removal for Self-Supervised Representation Learning. ICML Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen
2020	J	`jnl`	Automatic Shortcut Removal for Self-Supervised Representation Learning. CoRR Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen
2020	A*	`conf`	Disentangling Factors of Variations Using Few Labels. ICLR Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem
2020	A*	`conf`	High-Fidelity Generative Image Compression. NeurIPS Fabian Mentzer, George Toderici, Michael Tschannen, Eirikur Agustsson
2020	J	`jnl`	High-Fidelity Generative Image Compression. CoRR Fabian Mentzer, George Toderici, Michael Tschannen, Eirikur Agustsson
2020	A*	`conf`	Learning Better Lossless Compression Using Lossy Compression. CVPR Fabian Mentzer, Luc Van Gool, Michael Tschannen
2020	J	`jnl`	Learning Better Lossless Compression Using Lossy Compression. CoRR Fabian Mentzer, Luc Van Gool, Michael Tschannen
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	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`	Weakly-Supervised Disentanglement Without Compromises. ICML Francesco Locatello, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen
2020	J	`jnl`	Weakly-Supervised Disentanglement Without Compromises. CoRR Francesco Locatello, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen
2019	J	`jnl`	Disentangling Factors of Variation Using Few Labels. CoRR Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem
2019	A*	`conf`	Generative Adversarial Networks for Extreme Learned Image Compression. ICCV Eirikur Agustsson, Michael Tschannen, Fabian Mentzer, Radu Timofte, Luc Van Gool
2019	A*	`conf`	High-Fidelity Image Generation With Fewer Labels. ICML Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly
2019	J	`jnl`	High-Fidelity Image Generation With Fewer Labels. CoRR Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, 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 Full Resolution Learned Lossless Image Compression. CVPR Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool
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`	Semantic Bottleneck Scene Generation. CoRR Samaneh Azadi, Michael Tschannen, Eric Tzeng, Sylvain Gelly, Trevor Darrell, 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
2019	—	`—`	Unsupervised learning: model-based clustering and learned compression. Michael Tschannen
2018	J	`jnl`	Born Again Neural Networks. CoRR Tommaso Furlanello, Zachary C. Lipton, Michael Tschannen, Laurent Itti, Anima Anandkumar
2018	A*	`conf`	Born-Again Neural Networks. ICML Tommaso Furlanello, Zachary Chase Lipton, Michael Tschannen, Laurent Itti, Anima Anandkumar
2018	A*	`conf`	Conditional Probability Models for Deep Image Compression. CVPR Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool
2018	J	`jnl`	Conditional Probability Models for Deep Image Compression. CoRR Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool
2018	A*	`conf`	Deep Generative Models for Distribution-Preserving Lossy Compression. NeurIPS Michael Tschannen, Eirikur Agustsson, Mario Lucic
2018	J	`jnl`	Deep Generative Models for Distribution-Preserving Lossy Compression. CoRR Michael Tschannen, Eirikur Agustsson, Mario Lucic
2018	—	`conf`	Extreme Learned Image Compression with GANs. CVPR Workshops Eirikur Agustsson, Michael Tschannen, Fabian Mentzer, Radu Timofte, Luc Van Gool
2018	J	`jnl`	Generative Adversarial Networks for Extreme Learned Image Compression. CoRR Eirikur Agustsson, Michael Tschannen, Fabian Mentzer, Radu Timofte, Luc Van Gool
2018	J	`jnl`	Noisy Subspace Clustering via Matching Pursuits. IEEE Trans. Inf. Theory Michael Tschannen, Helmut Bölcskei
2018	J	`jnl`	Practical Full Resolution Learned Lossless Image Compression. CoRR Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool
2018	J	`jnl`	Recent Advances in Autoencoder-Based Representation Learning. CoRR Michael Tschannen, Olivier Bachem, Mario Lucic
2018	A*	`conf`	StrassenNets: Deep Learning with a Multiplication Budget. ICML Michael Tschannen, Aran Khanna, Animashree Anandkumar
2018	—	`conf`	Towards Image Understanding from Deep Compression Without Decoding. ICLR (Poster) Robert Torfason, Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool
2018	J	`jnl`	Towards Image Understanding from Deep Compression without Decoding. CoRR Robert Torfason, Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, Luc Van Gool
2017	A	`conf`	A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe. AISTATS Francesco Locatello, Rajiv Khanna, Michael Tschannen, Martin Jaggi
2017	J	`jnl`	A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe. CoRR Francesco Locatello, Rajiv Khanna, Michael Tschannen, Martin Jaggi
2017	—	`conf`	Convolutional Recurrent Neural Networks for Electrocardiogram Classification. CinC Martin Zihlmann, Dmytro Perekrestenko, Michael Tschannen
2017	J	`jnl`	Convolutional Recurrent Neural Networks for Electrocardiogram Classification. CoRR Martin Zihlmann, Dmytro Perekrestenko, Michael Tschannen
2017	—	`conf`	Deep structured features for semantic segmentation. EUSIPCO Michael Tschannen, Lukas Cavigelli, Fabian Mentzer, Thomas Wiatowski, Luca Benini
2017	—	`conf`	Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees. NIPS Francesco Locatello, Michael Tschannen, Gunnar Rätsch, Martin Jaggi
2017	J	`jnl`	Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees. CoRR Francesco Locatello, Michael Tschannen, Gunnar Rätsch, Martin Jaggi
2017	J	`jnl`	Soft-to-Hard Vector Quantization for End-to-End Learned Compression of Images and Neural Networks. CoRR Eirikur Agustsson, Fabian Mentzer, Michael Tschannen, Lukas Cavigelli, Radu Timofte, Luca Benini, Luc Van Gool
2017	—	`conf`	Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations. NIPS Eirikur Agustsson, Fabian Mentzer, Michael Tschannen, Lukas Cavigelli, Radu Timofte, Luca Benini, Luc Van Gool
2017	J	`jnl`	StrassenNets: Deep learning with a multiplication budget. CoRR Michael Tschannen, Aran Khanna, Anima Anandkumar
2016	J	`jnl`	Deep Structured Features for Semantic Segmentation. CoRR Michael Tschannen, Lukas Cavigelli, Fabian Mentzer, Thomas Wiatowski, Luca Benini
2016	A*	`conf`	Discrete Deep Feature Extraction: A Theory and New Architectures. ICML Thomas Wiatowski, Michael Tschannen, Aleksandar Stanic, Philipp Grohs, Helmut Bölcskei
2016	J	`jnl`	Discrete Deep Feature Extraction: A Theory and New Architectures. CoRR Thomas Wiatowski, Michael Tschannen, Aleksandar Stanic, Philipp Grohs, Helmut Bölcskei
2016	—	`conf`	Heart Sound Classification Using Deep Structured Features. CinC Michael Tschannen, Thomas Kramer, Gian Marti, Matthias Heinzmann, Thomas Wiatowski
2016	J	`jnl`	Noisy subspace clustering via matching pursuits. CoRR Michael Tschannen, Helmut Bölcskei
2016	J	`jnl`	Pursuits in Structured Non-Convex Matrix Factorizations. CoRR Rajiv Khanna, Michael Tschannen, Martin Jaggi
2016	J	`jnl`	Regression forest-based automatic estimation of the articular margin plane for shoulder prosthesis planning. Medical Image Anal. Michael Tschannen, Lazaros Vlachopoulos, Christian Gerber, Gábor Székely, Philipp Fürnstahl
2016	J	`jnl`	Robust nonparametric nearest neighbor random process clustering. CoRR Michael Tschannen, Helmut Bölcskei
2015	J	`jnl`	Dimensionality-reduced subspace clustering. CoRR Reinhard Heckel, Michael Tschannen, Helmut Bölcskei
2015	J	`jnl`	Nonparametric Nearest Neighbor Random Process Clustering. CoRR Michael Tschannen, Helmut Bölcskei
2015	B	`conf`	Nonparametric nearest neighbor random process clustering. ISIT Michael Tschannen, Helmut Bölcskei
2014	B	`conf`	Subspace clustering of dimensionality-reduced data. ISIT Reinhard Heckel, Michael Tschannen, Helmut Bölcskei
2014	J	`jnl`	Subspace clustering of dimensionality-reduced data. CoRR Reinhard Heckel, Michael Tschannen, Helmut Bölcskei
2013	—	`conf`	A Learning-Based Approach for Fast and Robust Vessel Tracking in Long Ultrasound Sequences. MICCAI (1) Valeria De Luca, Michael Tschannen, Gábor Székely, Christine Tanner
2012	—	`conf`	SecureSafe: a highly secure online data safe industrial use case. MPM@EuroSys Marc Rennhard, Michael Tschannen, Tobias Christen
2012	—	`conf`	Single Marker Localization for Automatic Patient Registration in Interventional Radiology. CURAC Michael Tschannen, Grzegorz Toporek, Daphné Wallach, Matthias Peterhans, Stefan Weber