publications
This page is updated periodically and may not always reflect the most recent publications. Group members are in italic. Last update: March 2 2026.
Legend: pre-print conference workshop journal miscellaneous
2026
Predict-Project-Renoise: Sampling Diffusion Models under Hard Constraints
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and .
pre-print
2025
Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation
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, Ruben Ohana, Michael McCabe, , François Lanusse, Shirley Ho.
NeurIPS 2025
Appa: Bending weather dynamics with latent diffusion models for global data assimilation
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, , , , , Matthias Pirlet, , Marilaure Grégoire, .
ML4PS workshop, NeurIPS 2025
Enforcing governing equation constraints in neural PDE solvers via training-free projections
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and .
ML4PS workshop, NeurIPS 2025
Training-Free Data Assimilation with GenCast
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, , and .
CCAI workshop, NeurIPS 2025
Panchromatic characterization of the Y0 brown dwarf WISEP J173835.52+273258.9 using JWST/MIRI
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, Paul Mollière, Helena Kühnle, Olivier Absil, , Rens Waters, Manuel Güdel, Thomas Henning, David Barrado, Leen Decin, John Pye, Pascal Tremblin.
pre-print
A Neural Material Point Method for Particle-based Simulations
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Omer Rochman Sharabi, Sacha Lewin, and .
TMLR
2024
Low-Budget Simulation-Based Inference with Bayesian Neural Networks
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, Maxence de la Brassinne Bonardeaux, Siddharth Mishra-Sharma, and .
pre-print
Learning Diffusion Priors from Observations by Expectation Maximization
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, , François Lanusse, and .
NeurIPS 2024
Grasping under Uncertainties: Sequential Neural Ratio Estimation for 6-DoF Robotic Grasping
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, Olivier Bruls, and .
IEEE Robotics and Automation Letters
2023
Score-based Data Assimilation
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and .
NeurIPS 2023
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability
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Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, , , , Alexandros Kalousis.
NeurIPS 2023
Robust Ocean Subgrid-Scale Parameterizations Using Fourier Neural Operators
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and .
ML4PS workshop, NeurIPS 2023
Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model
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and .
ML4PS workshop, NeurIPS 2023
Trick or treat? Evaluating stability strategies in graph network-based simulators
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and .
ML4PS workshop, NeurIPS 2023
Dynamic NeRFs for Soccer Scenes
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, Maxime Vandegar, Thomas Hoyoux, Olivier Barnich, .
6th International Workshop on Multimedia Content Analysis in Sports
Balancing Simulation-based Inference for Conservative Posteriors
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, Benjamin Kurt Miller, Patrick Forré, Christoph Weniger, .
AABI 2023
Neural posterior estimation for exoplanetary atmospheric retrieval
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, , Olivier Absil, Paul Mollière, Evert Nasedkin, .
Astronomy & Astrophysics
Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping
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, Julien Gustin, Olivier Brüls, .
Geometric Representations workshop, ICRA 2023
Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks
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Thibaut Théate, , Adrien Bolland, , and Damien Ernst.
Neurocomputing
2022
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation
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, , , , .
NeurIPS 2022
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful
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, , , , and .
TMLR
A deep learning approach for focal-plane wavefront sensing using vortex phase diversity
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, Gilles Orban de Xivry, , Olivier Absil.
Astronomy & Astrophysics
Simulation-based Bayesian inference for robotic grasping
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, Olivier Bruls, .
PRDL workshop, IROS 2022
A simulator-based autoencoder for focal plane wavefront sensing
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, Gilles Orban de Xivry, Olivier Absil, .
SPIE Astronomical Telescopes + Instrumentation
Robust Hybrid Learning With Expert Augmentation
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, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, , Jörn-Henrik Jacobsen.
TMLR
2021
Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference
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and .
ML4PS workshop, NeurIPS 2021
SAE: Sequential Anchored Ensembles
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and .
Bayesian Deep Learning workshop, NeurIPS 2021>
Towards constraining warm dark matter with stellar streams through neural simulation-based inference
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, Nilanjan Banik, Christophe Weniger, Gianfranco Bertone, and .
Monthly Notices of the Royal Astronomical Society
Simulation-based Bayesian inference for multi-fingered robotic grasping
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, Olivier Bruls, .
pre-print
Focal Plane Wavefront Sensing using Machine Learning: Performance of Convolutional Neural Networks compared to Fundamental Limits
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Gilles Orban de Xivry, , Pierre-Olivier Vanberg, Olivier Absil, and .
Monthly Notices of the Royal Astronomical Society
Diffusion Priors In Variational Autoencoders
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and .
INNF workshop, ICML 2021
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
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Maxime Vandegar, Michael Kagan, , and .
AISTATS 2021
Graphical Normalizing Flows
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and
AISTATS 2021
2020
Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization
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et al.
ML4PS workshop, NeurIPS 2020
Likelihood-free MCMC with Amortized Approximate Ratio Estimators
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, Volodimir Begy, and .
ICML 2020
You Say Normalizing Flows I see Bayesian Networks
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Antoine Wehenkel and
INNF workshop, ICML 2020
2019
Unconstrained Monotonic Neural Networks
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and
NeurIPS 2019
Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning
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Johann Brehmer, Siddharth Mishra-Sharma, , , and Kyle Cranmer
The Astrophysical Journal
Adversarial Variational Optimization of Non-Differentiable Simulators
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, , and Kyle Cranmer
AISTATS 2019
2018
Recurrent machines for likelihood-free inference
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Arthur Pesah, , and .
2nd workshop on meta-learning, NeurIPS 2018
Gradient Energy Matching for Distributed Asynchronous Gradient Descent
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,
pre-print