| Signal propagation in transformers: Theoretical perspectives and the role of rank collapse L Noci, S Anagnostidis, L Biggio, A Orvieto, SP Singh, A Lucchi Advances in Neural Information Processing Systems 35, 27198-27211, 2022 | 72 | 2022 |
| Dynamic context pruning for efficient and interpretable autoregressive transformers S Anagnostidis, D Pavllo, L Biggio, L Noci, A Lucchi, T Hofmann Advances in Neural Information Processing Systems 36, 2024 | 49 | 2024 |
| Adversarial learning for debiasing knowledge graph embeddings M Arduini, L Noci, F Pirovano, C Zhang, YR Shrestha, B Paudel arXiv preprint arXiv:2006.16309, 2020 | 42 | 2020 |
| Achieving a better stability-plasticity trade-off via auxiliary networks in continual learning S Kim, L Noci, A Orvieto, T Hofmann Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 37 | 2023 |
| Precise characterization of the prior predictive distribution of deep ReLU networks L Noci, G Bachmann, K Roth, S Nowozin, T Hofmann Advances in Neural Information Processing Systems 34, 20851-20862, 2021 | 37 | 2021 |
| The shaped transformer: Attention models in the infinite depth-and-width limit L Noci, C Li, M Li, B He, T Hofmann, CJ Maddison, D Roy Advances in Neural Information Processing Systems 36, 2024 | 35 | 2024 |
| Disentangling the roles of curation, data-augmentation and the prior in the cold posterior effect L Noci, K Roth, G Bachmann, S Nowozin, T Hofmann Advances in neural information processing systems 34, 12738-12748, 2021 | 24 | 2021 |
| Depthwise hyperparameter transfer in residual networks: Dynamics and scaling limit B Bordelon, L Noci, MB Li, B Hanin, C Pehlevan arXiv preprint arXiv:2309.16620, 2023 | 20 | 2023 |
| The curious case of benign memorization S Anagnostidis, G Bachmann, L Noci, T Hofmann arXiv preprint arXiv:2210.14019, 2022 | 12 | 2022 |
| How tempering fixes data augmentation in bayesian neural networks G Bachmann, L Noci, T Hofmann International Conference on Machine Learning (ICML), 2022 | 10 | 2022 |
| Super Consistency of Neural Network Landscapes and Learning Rate Transfer L Noci, A Meterez, T Hofmann, A Orvieto The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | 8* | 2024 |
| Disentangling Linear Mode-Connectivity GS Altintas, G Bachmann, L Noci, T Hofmann arXiv preprint arXiv:2312.09832, 2023 | 6 | 2023 |
| Understanding and Minimising Outlier Features in Neural Network Training B He, L Noci, D Paliotta, I Schlag, T Hofmann arXiv preprint arXiv:2405.19279, 2024 | 4 | 2024 |
| How Good is a Single Basin? K Lion, L Noci, T Hofmann, G Bachmann International Conference on Artificial Intelligence and Statistics, 4015-4023, 2024 | 2 | 2024 |
| Understanding and Minimising Outlier Features in Transformer Training B He, L Noci, D Paliotta, I Schlag, T Hofmann The Thirty-eighth Annual Conference on Neural Information Processing Systems, 0 | 1 | |
| Feature Learning Dynamics under Grokking in a Sparse Parity Task FJS Bautiste, G Bachmann, B He, L Noci, T Hofmann ICML 2024 HiLD Workshop on High-dimensional Learning Dynamics, 2024 | | 2024 |
| Exploring the Limits of Feature Learning in Continual Learning J Graldi, G Lanzillotta, L Noci, BF Grewe, T Hofmann NeurIPS 2024 Workshop on Scalable Continual Learning for Lifelong Foundation …, 2024 | | 2024 |
| How to scale-up? Foundations for Science of Scaling in Deep Learning L Noci training 69, 70, 0 | | |
| Unveiling Grokking: Analyzing Feature Learning Dynamics During Training JS Baustiste, G Bachmann, B He, L Noci, T Hofmann High-dimensional Learning Dynamics 2024: The Emergence of Structure and …, 0 | | |
Thomas HofmannProfessor of Computer Science, ETH ZurichAdresse e-mail validée de inf.ethz.ch