Antoine Wehenkel

Orcid: 0000-0001-5022-3999

According to our database1, Antoine Wehenkel authored at least 21 papers between 2017 and 2024.

Collaborative distances:

Timeline

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Bibliography

2024
Leveraging Cardiovascular Simulations for In-Vivo Prediction of Cardiac Biomarkers.
CoRR, 2024

Addressing Misspecification in Simulation-based Inference through Data-driven Calibration.
CoRR, 2024

2023
Robust Hybrid Learning With Expert Augmentation.
Trans. Mach. Learn. Res., 2023

Distributional reinforcement learning with unconstrained monotonic neural networks.
Neurocomputing, 2023

Simulation-based Inference for Cardiovascular Models.
CoRR, 2023

Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Inductive Bias In Deep Probabilistic Modelling.
PhD thesis, 2022

A Crisis In Simulation-Based Inference? Beware, Your Posterior Approximations Can Be Unfaithful.
Trans. Mach. Learn. Res., 2022

Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Averting A Crisis In Simulation-Based Inference.
CoRR, 2021

Diffusion Priors In Variational Autoencoders.
CoRR, 2021

Deep generative modeling for probabilistic forecasting in power systems.
CoRR, 2021

A Probabilistic Forecast-Driven Strategy for a Risk-Aware Participation in the Capacity Firming Market.
CoRR, 2021

Graphical Normalizing Flows.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Parameter Estimation of Three-Phase Untransposed Short Transmission Lines From Synchrophasor Measurements.
IEEE Trans. Instrum. Meas., 2020

Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization.
CoRR, 2020

You say Normalizing Flows I see Bayesian Networks.
CoRR, 2020

2019
Unconstrained Monotonic Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Recurrent machines for likelihood-free inference.
CoRR, 2018

2017
An App-based Algorithmic Approach for Harvesting Local and Renewable Energy using Electric Vehicles.
Proceedings of the 9th International Conference on Agents and Artificial Intelligence, 2017


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