| Unconstrained Monotonic Neural Networks A Wehenkel, G Louppe Neural Information Processing Systems 2019 33, 2019 | 202 | 2019 |
| A Crisis In Simulation-Based Inference? Beware, Your Posterior Approximations Can Be Unfaithful J Hermans, A Delaunoy, F Rozet, A Wehenkel, V Begy, G Louppe Transactions on Machine Learning Research, 2022 | 107* | 2022 |
| A deep generative model for probabilistic energy forecasting in power systems: normalizing flows J Dumas, A Wehenkel, D Lanaspeze, B Cornélusse, A Sutera Applied Energy 305, 117871, 2022 | 91 | 2022 |
| Introducing neuromodulation in deep neural networks to learn adaptive behaviours N Vecoven, D Ernst, A Wehenkel, G Drion PloS one 15 (1), e0227922, 2020 | 53 | 2020 |
| Parameter estimation of three-phase untransposed short transmission lines from synchrophasor measurements A Wehenkel, A Mukhopadhyay, JY Le Boudec, M Paolone IEEE Transactions on Instrumentation and Measurement 69 (9), 6143-6154, 2020 | 52 | 2020 |
| Graphical normalizing flows A Wehenkel, G Louppe International Conference on Artificial Intelligence and Statistics 2021, 37--45, 2020 | 41 | 2020 |
| Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference M Vandegar, M Kagan, A Wehenkel, G Louppe International Conference on Artificial Intelligence and Statistics 2021, 2020 | 32 | 2020 |
| Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation A Delaunoy, J Hermans, F Rozet, A Wehenkel, G Louppe Neural Information Processing Systems 2022, 2022 | 31 | 2022 |
| Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization A Delaunoy, A Wehenkel, T Hinderer, S Nissanke, C Weniger, ... Machine Learning and the Physical Sciences Workshop at NeurIPS2020, 2020 | 31 | 2020 |
| Diffusion priors in variational autoencoders A Wehenkel, G Louppe INNF+ Workshop @ ICML2021, 2021 | 25 | 2021 |
| A probabilistic forecast-driven strategy for a risk-aware participation in the capacity firming market J Dumas, C Cointe, A Wehenkel, A Sutera, X Fettweis, B Cornélusse IEEE Transactions on Sustainable Energy 13 (2), 1234-1243, 2021 | 20 | 2021 |
| Robust Hybrid Learning With Expert Augmentation A Wehenkel, J Behrmann, H Hsu, G Sapiro, G Louppe, JH Jacobsen Transactions on Machine Learning Research, 2022 | 14* | 2022 |
| A trust crisis in simulation-based inference J Hermans, A Delaunoy, F Rozet, A Wehenkel, V Begy, G Louppe Your posterior approximations can be unfaithful, 2021 | 13 | 2021 |
| An app-based algorithmic approach for harvesting local and renewable energy using electric vehicles A Dubois*, A Wehenkel*, R Fonteneau, F Olivier, D Ernst Proceedings of the 9th International Conference on Agents and Artificial …, 2017 | 12 | 2017 |
| You say Normalizing Flows I see Bayesian Networks A Wehenkel, G Louppe INNF+ Workshop @ ICML2020, 2020 | 11 | 2020 |
| Simulation-based inference for cardiovascular models A Wehenkel, J Behrmann, AC Miller, G Sapiro, O Sener, M Cuturi, ... arXiv preprint arXiv:2307.13918, 2023 | 9 | 2023 |
| Distributional reinforcement learning with unconstrained monotonic neural networks T Théate, A Wehenkel, A Bolland, G Louppe, D Ernst Neurocomputing 534, 199-219, 2023 | 9 | 2023 |
| Calibrating neural simulation-based inference with differentiable coverage probability M Falkiewicz, N Takeishi, I Shekhzadeh, A Wehenkel, A Delaunoy, ... Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
| Recurrent machines for likelihood-free inference A Pesah*, A Wehenkel*, G Louppe MetaLearn Workshop @ NeurIPS2018, 2018 | 7 | 2018 |
| Addressing Misspecification in Simulation-based Inference through Data-driven Calibration A Wehenkel, JL Gamella, O Sener, J Behrmann, G Sapiro, M Cuturi, ... arXiv preprint arXiv:2405.08719, 2024 | 5 | 2024 |
Arnaud DelaunoyPhD student, University of LiègeVerified email at uliege.be
