Papers
See also Google Scholar, ORCID or ORBi.
2024
A Neural Material Point Method for Particle-based Simulations
Omer Rochman Sharabi, Sacha Lewin, Gilles Louppe.
Pre-print.
arXiv:2408.15753 [PDF]
Low-Budget Simulation-Based Inference with Bayesian Neural Networks
Arnaud Delaunoy, Maxence de la Brassinne Bonardeaux, Siddharth Mishra-Sharma, Gilles Louppe.
Pre-print.
arXiv:2408.15136 [PDF]
Simulation-Based Inference Benchmark for LSST Weak Lensing Cosmology
Justine Zeghal, Denise Lanzieri, François Lanusse, Alexandre Boucaud, Gilles Louppe, Eric Aubourg, Adrian E Bayer, The LSST Collaboration
Pre-print.
arXiv:2409.17975 [PDF]
Learning Diffusion Priors from Observations by Expectation Maximization
François Rozet, Gérome Andry, François Lanusse, Gilles Louppe.
NeurIPS 2024.
arXiv:2405.13712 [PDF]
Video-Driven Graph Network-Based Simulators
Franciszek Szewczyk, Gilles Louppe, Matthia Sabatelli.
ML4PS workshop, NeurIPS 2024.
arXiv:2409.15344 [PDF]
Grasping under Uncertainties: Sequential Neural Ratio Estimation for 6-DoF Robotic Grasping
Norman Marlier, Olivier Bruls, Gilles Louppe.
IEEE Robotics and Automation Letters.
doi:10.1109/LRA.2024.3416773 [PDF]
Neural network-based simulation of fields and losses in electrical machines with ferromagnetic laminated cores
Florent Purnode, François Henrotte, Gilles Louppe, Christophe Geuzaine.
International Journal of Numerical Modelling.
doi:10.1002/jnm.3226 [PDF]
Harnessing machine learning for accurate treatment of overlapping opacity species in GCMs
Aaron David Schneider, Paul Mollière, Gilles Louppe, Ludmila Carone, Uffe Gråe Jørgensen, Leen Decin, Christiane Helling.
Astronomy & Astrophysics.
doi:10.1051/0004-6361/202348221 [PDF]
Deep generative models for fast photon shower simulation in ATLAS
The ATLAS collaboration.
Computing and Software for Big Science.
doi:10.1007/s41781-023-00106-9
2023
Score-based Data Assimilation
François Rozet, Gilles Louppe.
NeurIPS 2023.
arXiv:2306.10574 [PDF]
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability
Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis.
NeurIPS 2023.
arXiv:2310.13402 [PDF]
Robust Ocean Subgrid-Scale Parameterizations Using Fourier Neural Operators
Victor Mangeleer, Gilles Louppe.
ML4PS workshop, NeurIPS 2023.
arXiv:2310.02691 [PDF]
Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model
François Rozet, Gilles Louppe.
ML4PS workshop, NeurIPS 2023.
arXiv:2310.01853 [PDF]
Trick or treat? Evaluating stability strategies in graph network-based simulators
Omer Rochman, Gilles Louppe.
ML4PS workshop, NeurIPS 2023.
https://hdl.handle.net/2268/309361 [PDF]
Dynamic NeRFs for Soccer Scenes
Sacha Lewin, Maxime Vandegar, Thomas Hoyoux, Olivier Barnich, Gilles Louppe.
6th International Workshop on Multimedia Content Analysis in Sports.
arXiv:2309.06802 [PDF]
Balancing Simulation-based Inference for Conservative Posteriors
Arnaud Delaunoy, Benjamin Kurt Miller, Patrick Forré, Christoph Weniger, Gilles Louppe.
AABI 2023.
arXiv:2304.10978 [PDF]
Graph-informed simulation-based inference for models of active matter
Namid R Stillman, Silke Henkes, Roberto Mayor, Gilles Louppe.
ML4Materials workshop, ICLR 2023.
arXiv:2304.06806 [PDF]
Neural posterior estimation for exoplanetary atmospheric retrieval
Malavika Vasist, François Rozet, Olivier Absil, Paul Mollière, Evert Nasedkin, Gilles Louppe.
Astronomy & Astrophysics.
arXiv:10.1051/0004-6361/202245263 [PDF]
Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping
Norman Marlier, Julien Gustin, Olivier Brüls, Gilles Louppe.
Geometric Representations workshop, ICRA 2023.
arXiv:2304.08805 [PDF]
Policy Gradient Algorithms Implicitly Optimize by Continuation
Adrien Bolland, Gilles Louppe, Damien Ernst.
TMLR.
arXiv:2305.06851 [PDF]
Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks
Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, and Damien Ernst.
Neurocomputing.
doi:10.1016/j.neucom.2023.02.049 [PDF]
Cracking the genetic code with neural networks
Marc Joiret, Marine Leclercq, Gaspard Lambrechts, Francesca Rapino, Pierre Close, Gilles Louppe, Liesbet Geris.
Frontiers in Artificial Intelligence.
doi:10.3389/frai.2023.1128153 [PDF]
Adaptive Self-Training for Object Detection
Renaud Vandeghen, Gilles Louppe, Marc Van Droogenbroeck.
ICCV workshops 2023.
arXiv:2212.05911 [PDF]
2022
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation
Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe.
NeurIPS 2022.
arXiv:2208.13624 [PDF]
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful
Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, and Gilles Louppe.
TMLR.
arXiv:2110.06581 [PDF]
A deep learning approach for focal-plane wavefront sensing using vortex phase diversity
Maxime Quesnel, Gilles Orban de Xivry, Gilles Louppe, Olivier Absil.
Astronomy & Astrophysics.
doi:10.1051/0004-6361/202143001 [PDF]
Simulation-based Bayesian inference for robotic grasping
Norman Marlier, Olivier Bruls, Gilles Louppe.
PRDL workshop, IROS 2022.
openreview.net:q7vnfJK4UBo [PDF]
Bayesian uncertainty quantification for machine-learned models in physics
Yarin Gal, Petros Koumoutsakos, Francois Lanusse, Gilles Louppe, Costas Papadimitriou.
Nature Reviews Physics.
doi:10.1038/s42254-022-00498-4 [PDF]
A simulator-based autoencoder for focal plane wavefront sensing
Maxime Quesnel, Gilles Orban de Xivry, Olivier Absil, Gilles Louppe.
SPIE Astronomical Telescopes + Instrumentation.
doi:10.1117/12.2629476 [PDF]
Robust Hybrid Learning With Expert Augmentation
Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Jörn-Henrik Jacobsen.
TMLR.
arXiv:2202.03881 [PDF]
A hybrid stochastic model and its Bayesian identification for infectious disease screening in a university campus with application to massive COVID-19 screening at the University of Liège
Maarten Arnst, Gilles Louppe, Romain Van Hulle, Laurent Gillet, Fabrice Bureau, Vincent Denoël.
Mathematical Biosciences.
doi:10.1016/j.mbs.2022.108805 [PDF]
Decision-based interactive model to determine re-opening conditions of a large university campus in Belgium during the first COVID-19 wave
Vincent Denoël, Olivier Bruyère, Gilles Louppe, Fabrice Bureau, Vincent D’orio, Sébastien Fontaine, Laurent Gillet, Michèle Guillaume, Éric Haubruge, Anne-Catherine Lange, Fabienne Michel, Romain Van Hulle, Maarten Arnst, Anne-Françoise Donneau, Claude Saegerman.
Archives of Public Health.
doi:10.1186/s13690-022-00801-w [PDF]
2021
HNPE: Leveraging Global Parameters for Flow-based Neural Posterior Estimation
Pedro L. C. Rodrigues, Thomas Moreau, Gilles Louppe, and Alexandre Gramfort.
NeurIPS 2021.
arXiv:2102.06477 [PDF]
Truncated Marginal Neural Ratio Estimation
Benjamin Miller, Alex Cole, Patrick Forré, Gilles Louppe, and Christophe Weniger.
NeurIPS 2021.
arXiv:2107.01214 [PDF]
From global to local MDI variable importances for random forests and when they are Shapley values
Antonio Sutera, Gilles Louppe, Van Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
NeruIPS 2021.
arXiv:2111.02218 [PDF]
Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference
François Rozet and Gilles Louppe.
ML4PS workshop, NeurIPS 2021.
arXiv:2110.00449 [PDF]
SAE: Sequential Anchored Ensembles
Arnaud Delaunoy, Gilles Louppe.
Bayesian Deep Learning workshop, NeurIPS 2021.
arXiv:2201.00649 [PDF]
Towards constraining warm dark matter with stellar streams through neural simulation-based inference
Joeri Hermans, Nilanjan Banik, Christophe Weniger, Gianfranco Bertone, and Gilles Louppe.
Monthly Notices of the Royal Astronomical Society.
doi:10.1093/mnras/stab2181 [PDF]
Simulation-based Bayesian inference for multi-fingered robotic grasping
Norman Marlier, Olivier Bruls, Gilles Louppe.
Pre-print.
arXiv:2109.14275 [PDF]
Focal Plane Wavefront Sensing using Machine Learning: Performance of Convolutional Neural Networks compared to Fundamental Limits
Gilles Orban de Xivry, Maxime Quesnel, Pierre-Olivier Vanberg, Olivier Absil, and Gilles Louppe.
Monthly Notices of the Royal Astronomical Society.
doi:10.1093/mnras/stab1634 [PDF]
Diffusion Priors In Variational Autoencoders
Antoine Wehenkel and Gilles Louppe.
INNF workshop, ICML 2021.
arXiv:2106.15671 [PDF]
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
Maxime Vandegar, Michael Kagan, Antoine Wehenkel, and Gilles Louppe.
AISTATS 2021.
arXiv:2011.05836 [PDF]
Graphical Normalizing Flows
Antoine Wehenkel and Gilles Louppe
AISTATS 2021.
arXiv:2006.02548 [PDF]
Toward Machine Learning Optimization of Experimental Design
Atılım Güneş Baydin et al.
Nuclear Physics News.
doi:10.1080/10619127.2021.1881364 [PDF]
2020
Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time
Benjamin Kurt Miller, Alex Cole, Gilles Louppe, and Christophe Weniger.
ML4PS workshop, NeurIPS 2020.
arXiv:2011.13951 [PDF]
Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization
Arnaud Delaunoy et al.
ML4PS workshop, NeurIPS 2020.
arXiv:2010.12931 [PDF]
Improving the RSM map exoplanet detection algorithm
C.-H. Dahlqvist, Gilles Louppe, Olivier Absil
Astronomy & Astrophysics.
doi:10.1051/0004-6361/202039597 [PDF]
Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Joeri Hermans, Volodimir Begy, and Gilles Louppe.
ICML 2020.
http://proceedings.mlr.press/v119/hermans20a [PDF]
The Deep Quality-Value Family of Deep Reinforcement Learning Algorithms
Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco Wiering
IJCNN 2020.
doi:10.1109/IJCNN48605.2020.9206677 [PDF]
You Say Normalizing Flows I see Bayesian Networks
Antoine Wehenkel and Gilles Louppe
INNF workshop, ICML 2020.
arXiv:2006.00866 [PDF]
The frontier of simulation-based inference
Kyle Cranmer, Johann Brehmer, and Gilles Louppe
PNAS.
doi:10.1073/pnas.1912789117 [PDF]
Mining gold from implicit models to improve likelihood-free inference
Johann Brehmer, Gilles Louppe, Juan Pavez, Kyle Cranmer
PNAS.
doi:10.1073/pnas.1915980117 [PDF]
2019
Unconstrained Monotonic Neural Networks
Antoine Wehenkel and Gilles Louppe
NeurIPS 2019.
arXiv:1908.05164 [PDF]
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
Atilim Gunes Baydin et al.
NeurIPS 2019.
arXiv:1807.07706 [PDF]
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Atılım Güneş Baydin et al.
Supercomputing 2019.
arXiv:1907.03382 [PDF]
Machine learning for image-based wavefront sensing
Pierre-Olivier Vanberg, Gilles Orban de Xivry, Olivier Absil, and Gilles Louppe
ML4PS workshop, NeurIPS 2019.
http://hdl.handle.net/2268/241443 [PDF]
Mining gold: Improving simulation-based inference with latent information
Johann Brehmer, Kyle Cranmer, Siddharth Mishra-Sharma, Felix Kling, and Gilles Louppe
ML4PS workshop, NeurIPS 2019.
http://hdl.handle.net/2268/241748 [PDF]
Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning
Johann Brehmer, Siddharth Mishra-Sharma, Joeri Hermans, Gilles Louppe, and Kyle Cranmer
The Astrophysical Journal.
arXiv:1909.02005 [PDF]
Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms
Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A Wiering
DRL workshop, NeurIPS 2019.
arXiv:1909.01779 [PDF]
Effective LHC measurements with matrix elements and machine learning
Johann Brehmer, Kyle Cranmer, Irina Espejo, Felix Kling, Gilles Louppe, Juan Pavez
Journal of Physics: Conference Series.
arXiv:1906.01578 [PDF]
Adversarial Variational Optimization of Non-Differentiable Simulators
Gilles Louppe, Kyle Cranmer
AISTATS 2019.
arXiv:1707.07113 [PDF]
github:glouppe/paper-avo [code]
2018
Likelihood-free inference with an improved cross-entropy estimator
Markus Stoye, Johann Brehmer, Gilles Louppe, Juan Pavez, Kyle Cranmer
ML4PS workshop, NeurIPS 2018.
arXiv:1808.00973 [PDF]
Recurrent machines for likelihood-free inference
Arthur Pesah, Antoine Wehenkel and Gilles Louppe.
2nd workshop on meta-learning, NeurIPS 2018.
arXiv:1811.12932 [PDF]
Robust EEG-based cross-site and cross-protocol classification of states of consciousness
Denis Engemann et al.
Brain.
doi:10.1093/brain/awy251 [PDF]
Deep Quality-Value (DQV) Learning
Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering
BNAIC 2018.
arXiv:1810.00368 [PDF]
Deep generative models for fast shower simulation in ATLAS
The ATLAS collaboration
ATL-SOFT-PUB-2018-001.
https://cds.cern.ch/record/2630433 [PDF]
Machine Learning in High Energy Physics Community White Paper
Kim Albertsson et al.
Journal of Physics: Conference Series.
arXiv:1807.02876 [PDF]
Gradient Energy Matching for Distributed Asynchronous Gradient Descent
Joeri Hermans, Gilles Louppe
Pre-print.
arXiv:1805.08469 [PDF]
Constraining Effective Field Theories with Machine Learning
Johann Brehmer, Kyle Cranmer, Gilles Louppe, Juan Pavez
Physical Review Letters.
arXiv:1805.00013 [PDF]
A Guide to Constraining Effective Field Theories with Machine Learning
Johann Brehmer, Kyle Cranmer, Gilles Louppe, Juan Pavez
Physical Review D.
arXiv:1805.00020 [PDF]
Random Subspace with Trees for Feature Selection Under Memory Constraints
Antonio Sutera, Célia Chatel, Gilles Louppe, Louis Wehenkel, Pierre Geurts
AISTATS 2018.
arXiv:1709.01177 [PDF]
2017
Learning to Pivot with Adversarial Networks
Gilles Louppe, Michael Kagan, Kyle Cranmer
NeurIPS 2017.
arXiv:1611.01046 [PDF]
Neural Message Passing for Jet Physics
Isaac Henrion, Johann Brehmer, Joan Bruna, Kyunghun Cho, Kyle Cranmer, Gilles Louppe, Gaspar Rochette
Deep Learning for Physical Sciences workshop, NeurIPS 2017.
https://dl4physicalsciences.github.io/files/nips_dlps_2017_29.pdf [PDF]
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators
Mario Lezcano Casado, Atilim Gunes Baydin, David Martínez Rubio, Tuan Anh Le, Frank Wood, Lukas Heinrich, Gilles Louppe, Kyle Cranmer, Karen Ng, Wahid Bhimji
Deep Learning for Physical Sciences workshop, NeurIPS 2017.
arXiv:1712.07901 [PDF]
QCD-Aware Recursive Neural Networks for Jet Physics
Gilles Louppe, Kyunghyun Cho, Cyril Becot, Kyle Cranmer
Journal of High Energy Physics.
doi:10.1007/JHEP01(2019)057 [PDF]
github:glouppe/recnn [code]
2016
Unifying generative models and exact likelihood-free inference with conditional bijections
Kyle Cranmer, Gilles Louppe
Journal of brief ideas.
doi:10.5281/zenodo.198541 [PDF]
Experiments using machine learning to approximate likelihood ratios for mixture models
Kyle Cranmer, Juan Pavez, Gilles Louppe, WK Brooks
Journal of Physics: Conference Series.
doi:10.1088/1742-6596/762/1/012034 [PDF]
Context-dependent feature analysis with random forests
Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
UAI 2016.
https://www.auai.org/uai2016/proceedings/papers/253.pdf [PDF]
Cytomine: An open-source software for collaborative analysis of whole-slide images
Raphaël Marée, Loïc Rollus, Benjamin Stévens, Renaud Hoyoux, Gilles Louppe, Rémy Vandaele, Jean-Michel Begon, Pierre Geurts, Louis Wehenkel
European Congress on Digital Pathology.
doi:10.17629/www.diagnosticpathology.eu-2016-8:151 [PDF]
Visualization of publication impact
Eamonn Maguire, Javier Martin Montull, Gilles Louppe
EuroVis 2016.
https://arxiv.org/abs/1605.06242 [PDF]
Clusterix: a visual analytics approach to clustering
Eamonn Maguire, Ilias Koutsakis, Gilles Louppe
Symposium on Visualization in Data Science at IEEE VIS 2016.
http://dx.doi.org/10.13140/RG.2.2.18243.96805 [PDF]
Ethnicity sensitive author disambiguation using semi-supervised learning
Gilles Louppe, Hussein Al-Natsheh, Mateusz Susik, Eamonn Maguire
Knowledge Engineering and Semantic Web 2016.
arXiv:1508.07744 [PDF]
github:glouppe/paper-author-disambiguation [code]
2015
Approximating Likelihood Ratios with Calibrated Discriminative Classifiers
Kyle Cranmer, Juan Pavez, Gilles Louppe
Pre-print.
arXiv:1506.02169 [PDF]
Pitfalls of evaluating a classifier’s performance in high energy physics applications
Gilles Louppe, Tim Head
Pre-print.
https://zenodo.org/record/34934 [notebook]
Collaborative analysis of gigapixel images using Cytomine
Raphaël Marée, Loïc Rollus, Benjamin Stévens, Renaud Hoyoux, Jean-Michel Begon, Rémy Vandaele, Gilles Louppe, Pierre Geurts, Louis Wehenkel
14th International Congress for Stereology and Image Analysis.
http://popups.ulg.ac.be/0351-580X/index.php?id=3692&file=1&pid=3681 [PDF]
Scikit-learn: Machine Learning Without Learning the Machinery
Gael Varoquaux, Lars Buitinck, Gilles Louppe, Olivier Grisel, Fabian Pedregosa, Andreas Mueller
GetMobile: Mobile Computing and Communications.
https://dl.acm.org/citation.cfm?id=2786995 [PDF]
Solar Energy Prediction: An International Contest to Initiate Interdisciplinary Research on Compelling Meteorological Problems
Amy McGovern, David John Gagne II, Lucas Eustaquio, Gilberto Titericz Junior, Benjamin Lazorthes, Owen Zhang, Gilles Louppe, Peter Prettenhofer, Jeffrey Basara, Thomas Hamill, David Margolin
Bulletin of the American Meteorological Society.
http://hdl.handle.net/2268/177115 [PDF]
2014
Understanding Random Forests
Gilles Louppe
PhD thesis, University of Liège.
http://hdl.handle.net/2268/170309 [PDF]
github:glouppe/phd-thesis [code]
Simple connectome inference from partial correlation statistics in calcium imaging
Antonio Sutera, Arnaud Joly, Vincent François-Lavet, Zixiao Aaron Qiu, Gilles Louppe, Damien Ernst, Pierre Geurts
Chapter in “Neural Connectomics Challenge”, Springer.
http://hdl.handle.net/2268/169767 [PDF]
github:glouppe/kaggle-connectomics [code]
Exploiting SNP Correlations within Random Forest for Genome-Wide Association Studies
Vincent Botta, Gilles Louppe, Pierre Geurts, Louis Wehenkel
PLOS ONE.
http://dx.plos.org/10.1371/journal.pone.0093379 [PDF]
github:0asa/TTree-source [code]
A hybrid human-computer approach for large-scale image-based measurements using web services and machine learning
11th International Symposium on Biomedical Imaging.
Raphaël Marée, Loïc Rollus, Benjamin Stevens, Gilles Louppe, et al.
http://hdl.handle.net/2268/162084 [PDF]
2013
Understanding variable importances in forests of randomized trees
Gilles Louppe, Louis Wehenkel, Antonio Sutera, Pierre Geurts
NeurIPS 2013.
http://hdl.handle.net/2268/155642 [PDF]
github:glouppe/paper-variable-importances [code]
API design for machine learning software: experiences from the scikit-learn project
Lars Buitinck, Gilles Louppe, Mathieu Blondel, et al.
ECML/PKDD 2013.
http://hdl.handle.net/2268/154357 [PDF]
github:scikit-learn/scikit-learn [code]
2012
Scikit-Learn: Machine Learning in Python
Fabian Pedregosa et al.
Journal of Machine Learning Research.
arXiv:1201.0490 [PDF]
http://scikit-learn.org/stable/ [website]
Ensembles on Random Patches
Gilles Louppe, Pierre Geurts
ECML/PKDD 2012.
http://hdl.handle.net/2268/130099 [PDF]
2011
Learning to rank with extremely randomized trees
Pierre Geurts, Gilles Louppe
Proceedings of the Learning to Rank Challenge.
http://hdl.handle.net/2268/84538 [PDF]
2010
A zealous parallel gradient descent algorithm
Gilles Louppe, Pierre Geurts
Learning on Cores, Clusters and Clouds workshop, NeurIPS 2010.
http://hdl.handle.net/2268/80780 [PDF, code]
Collaborative filtering: Scalable approaches using restricted Boltzmann machines
Gilles Louppe
Master thesis, University of Liège.
http://hdl.handle.net/2268/74400 [PDF, code]
