| Born again neural networks T Furlanello, ZC Lipton, M Tschannen, L Itti, A Anandkumar International Conference on Machine Learning (ICML), 1602-1611, 2018 | 1446 | 2018 |
| Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities G Comanici, E Bieber, M Schaekermann, I Pasupat, N Sachdeva, I Dhillon, ... arXiv preprint arXiv:2507.06261, 2025 | 1337 | 2025 |
| Scaling vision transformers to 22 billion parameters M Dehghani, J Djolonga, B Mustafa, P Padlewski, J Heek, J Gilmer, ... International Conference on Machine Learning (ICML), 7480-7512, 2023 | 884 | 2023 |
| Generative adversarial networks for extreme learned image compression E Agustsson*, M Tschannen*, F Mentzer*, R Timofte, L Van Gool International Conference on Computer Vision (ICCV), 2019 | 805 | 2019 |
| Recent advances in autoencoder-based representation learning M Tschannen, O Bachem, M Lucic Workshop on Bayesian Deep Learning (NeurIPS 2018), 2018 | 707 | 2018 |
| On mutual information maximization for representation learning M Tschannen*, J Djolonga*, PK Rubenstein, S Gelly, M Lucic International Conference on Learning Representations (ICLR), 2020 | 696 | 2020 |
| Soft-to-hard vector quantization for end-to-end learning compressible representations E Agustsson, F Mentzer, M Tschannen, L Cavigelli, R Timofte, L Benini, ... Advances in Neural Information Processing Systems (NIPS), 1141-1151, 2017 | 690 | 2017 |
| High-Fidelity Generative Image Compression F Mentzer, G Toderici, M Tschannen, E Agustsson Advances in Neural Information Processing Systems (NeurIPS), 2020 | 655 | 2020 |
| Conditional probability models for deep image compression F Mentzer, E Agustsson, M Tschannen, R Timofte, L Van Gool IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 | 655 | 2018 |
| A large-scale study of representation learning with the visual task adaptation benchmark X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... arXiv preprint arXiv:1910.04867, 2019 | 612* | 2019 |
| PaliGemma: A versatile 3B VLM for transfer L Beyer, A Steiner, AS Pinto, A Kolesnikov, X Wang, D Salz, M Neumann, ... arXiv preprint arXiv:2407.07726, 2024 | 506 | 2024 |
| Weakly-supervised disentanglement without compromises F Locatello, B Poole, G Rätsch, B Schölkopf, O Bachem, M Tschannen International Conference on Machine Learning (ICML), 2020 | 456 | 2020 |
| Siglip 2: Multilingual vision-language encoders with improved semantic understanding, localization, and dense features M Tschannen, A Gritsenko, X Wang, MF Naeem, I Alabdulmohsin, ... arXiv preprint arXiv:2502.14786, 2025 | 396 | 2025 |
| Finite Scalar Quantization: VQ-VAE made simple F Mentzer, D Minnen, E Agustsson, M Tschannen International Conference on Learning Representations (ICLR), 2024 | 378 | 2024 |
| Convolutional recurrent neural networks for electrocardiogram classification M Zihlmann, D Perekrestenko, M Tschannen Computing in Cardiology Conference (CinC) 44, 2017 | 336 | 2017 |
| Practical full resolution learned lossless image compression F Mentzer, E Agustsson, M Tschannen, R Timofte, L Van Gool IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 298 | 2019 |
| PaLI-X: On scaling up a multilingual vision and language model X Chen, J Djolonga, P Padlewski, B Mustafa, S Changpinyo, J Wu, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024 | 290 | 2024 |
| Disentangling factors of variation using few labels F Locatello, M Tschannen, S Bauer, G Rätsch, B Schölkopf, O Bachem International Conference on Learning Representations (ICLR), 2020 | 229 | 2020 |
| Towards image understanding from deep compression without decoding R Torfason, F Mentzer, E Agustsson, M Tschannen, R Timofte, L Van Gool International Conference on Learning Representations (ICLR), 2018 | 219 | 2018 |
| High-fidelity image generation with fewer labels M Lucic*, M Tschannen*, M Ritter*, X Zhai, O Bachem, S Gelly International Conference on Machine Learning (ICML), 2019 | 196* | 2019 |
Fabian MentzerResearch Scientist at Google Deep MindVerified email at google.com
