Antoine Wehenkel

32 papers A* 4A 2Journal 23Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Addressing Misspecification in Simulation-based Inference through Data-driven Calibration. ICML Antoine Wehenkel, Juan L. Gamella, Ozan Sener, Jens Behrmann, Guillermo Sapiro, Jörn-Henrik Jacobsen, Marco Cuturi
2025	J	`jnl`	Hybrid Modeling of Photoplethysmography for Non-invasive Monitoring of Cardiovascular Parameters. CoRR Emanuele Palumbo, Sorawit Saengkyongam, Maria R. Cervera, Jens Behrmann, Andrew C. Miller, Guillermo Sapiro, Christina Heinze-Deml, Antoine Wehenkel
2025	J	`jnl`	Inferring Optical Tissue Properties from Photoplethysmography using Hybrid Amortized Inference. CoRR Jens Behrmann, Maria R. Cervera, Antoine Wehenkel, Andrew C. Miller, Albert Cerussi, Pranay Jain, Vivek Venugopal, Shijie Yan, Guillermo Sapiro, Luca Pegolotti, Jörn-Henrik Jacobsen
2024	J	`jnl`	Addressing Misspecification in Simulation-based Inference through Data-driven Calibration. CoRR Antoine Wehenkel, Juan L. Gamella, Ozan Sener, Jens Behrmann, Guillermo Sapiro, Marco Cuturi, Jörn-Henrik Jacobsen
2024	J	`jnl`	Leveraging Cardiovascular Simulations for In-Vivo Prediction of Cardiac Biomarkers. CoRR Laura Manduchi, Antoine Wehenkel, Jens Behrmann, Luca Pegolotti, Andy C. Miller, Ozan Sener, Marco Cuturi, Guillermo Sapiro, Jörn-Henrik Jacobsen
2023	A*	`conf`	Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. NeurIPS Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis
2023	J	`jnl`	Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. CoRR Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis
2023	J	`jnl`	Distributional reinforcement learning with unconstrained monotonic neural networks. Neurocomputing Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, Damien Ernst
2023	J	`jnl`	Robust Hybrid Learning With Expert Augmentation. Trans. Mach. Learn. Res. Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Jörn-Henrik Jacobsen
2023	J	`jnl`	Simulation-based Inference for Cardiovascular Models. CoRR Antoine Wehenkel, Jens Behrmann, Andrew C. Miller, Guillermo Sapiro, Ozan Sener, Marco Cuturi, Jörn-Henrik Jacobsen
2022	J	`jnl`	A Crisis In Simulation-Based Inference? Beware, Your Posterior Approximations Can Be Unfaithful. Trans. Mach. Learn. Res. Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Volodimir Begy, Gilles Louppe
2022	—	`—`	Inductive Bias In Deep Probabilistic Modelling. Antoine Wehenkel
2022	J	`jnl`	Robust Hybrid Learning With Expert Augmentation. CoRR Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Jörn-Henrik Jacobsen
2022	A*	`conf`	Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation. NeurIPS Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe
2022	J	`jnl`	Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation. CoRR Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe
2021	J	`jnl`	A Probabilistic Forecast-Driven Strategy for a Risk-Aware Participation in the Capacity Firming Market. CoRR Jonathan Dumas, Colin Cointe, Antoine Wehenkel, Antonio Sutera, Xavier Fettweis, Bertrand Cornélusse
2021	J	`jnl`	Averting A Crisis In Simulation-Based Inference. CoRR Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Gilles Louppe
2021	J	`jnl`	Deep generative modeling for probabilistic forecasting in power systems. CoRR Jonathan Dumas, Antoine Wehenkel, Damien Lanaspeze, Bertrand Cornélusse, Antonio Sutera
2021	J	`jnl`	Diffusion Priors In Variational Autoencoders. CoRR Antoine Wehenkel, Gilles Louppe
2021	J	`jnl`	Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks. CoRR Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, Damien Ernst
2021	A	`conf`	Graphical Normalizing Flows. AISTATS Antoine Wehenkel, Gilles Louppe
2021	A	`conf`	Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference. AISTATS Maxime Vandegar, Michael Kagan, Antoine Wehenkel, Gilles Louppe
2020	J	`jnl`	Graphical Normalizing Flows. CoRR Antoine Wehenkel, Gilles Louppe
2020	J	`jnl`	Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization. CoRR Arnaud Delaunoy, Antoine Wehenkel, Tanja Hinderer, Samaya Nissanke, Christoph Weniger, Andrew R. Williamson, Gilles Louppe
2020	J	`jnl`	Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference. CoRR Maxime Vandegar, Michael Kagan, Antoine Wehenkel, Gilles Louppe
2020	J	`jnl`	Parameter Estimation of Three-Phase Untransposed Short Transmission Lines From Synchrophasor Measurements. IEEE Trans. Instrum. Meas. Antoine Wehenkel, Arpan Mukhopadhyay, Jean-Yves Le Boudec, Mario Paolone
2020	J	`jnl`	You say Normalizing Flows I see Bayesian Networks. CoRR Antoine Wehenkel, Gilles Louppe
2019	—	`conf`	Unconstrained Monotonic Neural Networks. BNAIC/BENELEARN Antoine Wehenkel, Gilles Louppe
2019	A*	`conf`	Unconstrained Monotonic Neural Networks. NeurIPS Antoine Wehenkel, Gilles Louppe
2019	J	`jnl`	Unconstrained Monotonic Neural Networks. CoRR Antoine Wehenkel, Gilles Louppe
2018	J	`jnl`	Recurrent machines for likelihood-free inference. CoRR Arthur Pesah, Antoine Wehenkel, Gilles Louppe
2017	—	`conf`	An App-based Algorithmic Approach for Harvesting Local and Renewable Energy using Electric Vehicles. ICAART (1) Antoine Dubois, Antoine Wehenkel, Raphael Fonteneau, Frédéric Olivier, Damien Ernst