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Antoine Wehenkel
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2020 – today
- 2024
- [i16]Antoine Wehenkel, Juan L. Gamella, Ozan Sener, Jens Behrmann, Guillermo Sapiro, Marco Cuturi, Jörn-Henrik Jacobsen:
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration. CoRR abs/2405.08719 (2024) - 2023
- [j4]Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, Damien Ernst:
Distributional reinforcement learning with unconstrained monotonic neural networks. Neurocomputing 534: 199-219 (2023) - [j3]Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Jörn-Henrik Jacobsen:
Robust Hybrid Learning With Expert Augmentation. Trans. Mach. Learn. Res. 2023 (2023) - [c7]Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis:
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. NeurIPS 2023 - [i15]Antoine Wehenkel, Jens Behrmann, Andrew C. Miller, Guillermo Sapiro, Ozan Sener, Marco Cuturi, Jörn-Henrik Jacobsen:
Simulation-based Inference for Cardiovascular Models. CoRR abs/2307.13918 (2023) - [i14]Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis:
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. CoRR abs/2310.13402 (2023) - 2022
- [b1]Antoine Wehenkel:
Inductive Bias In Deep Probabilistic Modelling. University of Liège, Belgium, 2022 - [j2]Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Volodimir Begy, Gilles Louppe:
A Crisis In Simulation-Based Inference? Beware, Your Posterior Approximations Can Be Unfaithful. Trans. Mach. Learn. Res. 2022 (2022) - [c6]Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe:
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation. NeurIPS 2022 - [i13]Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Jörn-Henrik Jacobsen:
Robust Hybrid Learning With Expert Augmentation. CoRR abs/2202.03881 (2022) - [i12]Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe:
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation. CoRR abs/2208.13624 (2022) - 2021
- [c5]Antoine Wehenkel, Gilles Louppe:
Graphical Normalizing Flows. AISTATS 2021: 37-45 - [c4]Maxime Vandegar, Michael Kagan, Antoine Wehenkel, Gilles Louppe:
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference. AISTATS 2021: 2107-2115 - [i11]Jonathan Dumas, Colin Cointe, Antoine Wehenkel, Antonio Sutera, Xavier Fettweis, Bertrand Cornélusse:
A Probabilistic Forecast-Driven Strategy for a Risk-Aware Participation in the Capacity Firming Market. CoRR abs/2105.13801 (2021) - [i10]Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, Damien Ernst:
Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks. CoRR abs/2106.03228 (2021) - [i9]Jonathan Dumas, Antoine Wehenkel, Damien Lanaspeze, Bertrand Cornélusse, Antonio Sutera:
Deep generative modeling for probabilistic forecasting in power systems. CoRR abs/2106.09370 (2021) - [i8]Antoine Wehenkel, Gilles Louppe:
Diffusion Priors In Variational Autoencoders. CoRR abs/2106.15671 (2021) - [i7]Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Gilles Louppe:
Averting A Crisis In Simulation-Based Inference. CoRR abs/2110.06581 (2021) - 2020
- [j1]Antoine Wehenkel, Arpan Mukhopadhyay, Jean-Yves Le Boudec, Mario Paolone:
Parameter Estimation of Three-Phase Untransposed Short Transmission Lines From Synchrophasor Measurements. IEEE Trans. Instrum. Meas. 69(9): 6143-6154 (2020) - [i6]Antoine Wehenkel, Gilles Louppe:
You say Normalizing Flows I see Bayesian Networks. CoRR abs/2006.00866 (2020) - [i5]Antoine Wehenkel, Gilles Louppe:
Graphical Normalizing Flows. CoRR abs/2006.02548 (2020) - [i4]Arnaud Delaunoy, Antoine Wehenkel, Tanja Hinderer, Samaya Nissanke, Christoph Weniger, Andrew R. Williamson, Gilles Louppe:
Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization. CoRR abs/2010.12931 (2020) - [i3]Maxime Vandegar, Michael Kagan, Antoine Wehenkel, Gilles Louppe:
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference. CoRR abs/2011.05836 (2020)
2010 – 2019
- 2019
- [c3]Antoine Wehenkel, Gilles Louppe:
Unconstrained Monotonic Neural Networks. BNAIC/BENELEARN 2019 - [c2]Antoine Wehenkel, Gilles Louppe:
Unconstrained Monotonic Neural Networks. NeurIPS 2019: 1543-1553 - [i2]Antoine Wehenkel, Gilles Louppe:
Unconstrained Monotonic Neural Networks. CoRR abs/1908.05164 (2019) - 2018
- [i1]Arthur Pesah, Antoine Wehenkel, Gilles Louppe:
Recurrent machines for likelihood-free inference. CoRR abs/1811.12932 (2018) - 2017
- [c1]Antoine Dubois, Antoine Wehenkel, Raphael Fonteneau, Frédéric Olivier, Damien Ernst:
An App-based Algorithmic Approach for Harvesting Local and Renewable Energy using Electric Vehicles. ICAART (1) 2017: 322-327
Coauthor Index
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last updated on 2024-06-25 21:53 CEST by the dblp team
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