| Constant Curvature Graph Convolutional Networks G Bachmann, G Bécigneul, O Ganea International Conference on Machine Learning (ICML 2020), 486-496, 2020 | 132 | 2020 |
| Surface Defect Classification and Detection on Extruded Aluminum Profiles Using Convolutional Neural Networks FM Neuhauser, G Bachmann, P Hora International Journal of Material Forming 13, 591-603, 2020 | 52 | 2020 |
| 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 (NeurIPS 2021), 2021 | 31 | 2021 |
| Analytic Insights into Structure and Rank of Neural Network Hessian Maps SP Singh, G Bachmann, T Hofmann Advances in Neural Information Processing Systems (NeurIPS 2021), 2021 | 29 | 2021 |
| Clip-guided vision-language pre-training for question answering in 3d scenes M Parelli, A Delitzas, N Hars, G Vlassis, S Anagnostidis, G Bachmann, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 24 | 2023 |
| Scaling MLPs: A Tale of Inductive Bias G Bachmann, S Anagnostidis, T Hofmann Advances in Neural Information Processing Systems (NeurIPS 2023), 2023 | 20 | 2023 |
| 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 (NeurIPS 2021), 2021 | 19 | 2021 |
| Generalization Through The Lens Of Leave-One-Out Error G Bachmann, T Hofmann, A Lucchi International Conference on Learning Representations (ICLR 2022), 2022 | 13 | 2022 |
| Multi-clip: Contrastive vision-language pre-training for question answering tasks in 3d scenes A Delitzas, M Parelli, N Hars, G Vlassis, S Anagnostidis, G Bachmann, ... arXiv preprint arXiv:2306.02329, 2023 | 9 | 2023 |
| The Pitfalls of Next-Token Prediction G Bachmann, V Nagarajan arXiv preprint arXiv:2403.06963, 2024 | 7 | 2024 |
| The Curious Case of Benign Memorization S Anagnostidis, G Bachmann, L Noci, T Hofmann International Conference on Learning Representations (ICLR 2023), 2022 | 7 | 2022 |
| How Tempering Fixes Data Augmentation in Bayesian Neural Networks G Bachmann, L Noci, T Hofmann International Conference on Machine Learning (ICML 2022), 2022 | 7 | 2022 |
| Uniform Convergence, Adversarial Spheres and a Simple Remedy G Bachmann, SM Moosavi-Dezfooli, T Hofmann International Conference on Machine Learning (ICML 2021), 2021 | 7 | 2021 |
| Random Teachers are Good Teachers F Sarnthein, G Bachmann, S Anagnostidis, T Hofmann International Conference on Machine Learning (ICML 2023), 2023 | 5 | 2023 |
| Disentangling Linear Mode-Connectivity GS Altintas, G Bachmann, L Noci, T Hofmann arXiv preprint arXiv:2312.09832, 2023 | 3 | 2023 |
| Navigating Scaling Laws: Accelerating Vision Transformer's Training via Adaptive Strategies S Anagnostidis, G Bachmann, T Hofmann arXiv preprint arXiv:2311.03233, 2023 | 2 | 2023 |
| A Language Model's Guide Through Latent Space D von Rütte, S Anagnostidis, G Bachmann, T Hofmann arXiv preprint arXiv:2402.14433, 2024 | 1 | 2024 |
| EXPLAINTABLE: Explaining Large Scale Models Applied To Tabular Data JS Baustiste, T Engelmann, NP Montemayor, L Hart, G Lanzillotta, ... ICLR 2023 Workshop on Trustworthy and Reliable Large-Scale Machine Learning …, 0 | 1* | |
| How Good is a Single Basin? K Lion, L Noci, T Hofmann, G Bachmann AISTATS 2024, 2024 | | 2024 |
| Interpolated-MLPs: Controllable Inductive Bias S Wu, J Hong, G Bachmann High-dimensional Learning Dynamics 2024: The Emergence of Structure and …, 0 | | |
