| Repulsive Deep Ensembles are Bayesian F D'Angelo, V Fortuin NeurIPS 2021, 2021 | 126 | 2021 |
| Posterior meta-replay for continual learning C Henning, M Cervera, F D'Angelo, J Von Oswald, R Traber, B Ehret, ... Advances in neural information processing systems 34, 14135-14149, 2021 | 75 | 2021 |
| Learning the Ising model with generative neural networks F D'Angelo, L Böttcher Physical Review Research 2 (2), 023266, 2020 | 50 | 2020 |
| On Stein Variational Neural Network Ensembles F D'Angelo, V Fortuin, F Wenzel Workshop on Uncertainty & Robustness in Deep Learning (ICML), 2021 | 36 | 2021 |
| Annealed Stein Variational Gradient Descent F D’Angelo, V Fortuin 3rd Symposium on Advances in Approximate Bayesian Inference, 2020, 2020 | 31 | 2020 |
| Why do we need weight decay in modern deep learning? F D'Angelo, M Andriushchenko, A Varre, N Flammarion NeurIPS 2024, 2024 | 29* | 2024 |
| On out-of-distribution detection with Bayesian neural networks F D'Angelo, C Henning arXiv. org, 2021 | 18* | 2021 |
| Are Bayesian neural networks intrinsically good at out-of-distribution detection? C Henning, F D'Angelo, BF Grewe ICML 2021 Workshop on Uncertainty and Robustness in Deep Learning., 2021 | 16 | 2021 |
| Uncertainty estimation under model misspecification in neural network regression MR Cervera, R Dätwyler, F D'Angelo, H Keurti, BF Grewe, C Henning NeurIPS 2021 Workshop Your Model Is Wrong: Robustness and Misspecification …, 2021 | 6 | 2021 |
| Selective induction Heads: How Transformers Select Causal Structures in Context F D'Angelo, F Croce, N Flammarion ICLR 2025, 2025 | | 2025 |
| Why Do We Need Weight Decay for Overparameterized Deep Networks? F D'Angelo, A Varre, M Andriushchenko, N Flammarion NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning, 2023 | | 2023 |
Christian HenningEthonAI AGBestätigte E-Mail-Adresse bei ethon.ai
