Papers

2023

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.
arXiv:2311.00775 [PDF]

Robust Ocean Subgrid-Scale Parameterizations Using Fourier Neural Operators
Victor Mangeleer, Gilles Louppe.
arXiv:2310.02691 [PDF]

Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model
François Rozet, Gilles Louppe.
arXiv:2310.01853 [PDF]

Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability
Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis.
arXiv:2310.13402 [PDF]

Trick or treat? Evaluating stability strategies in graph network-based simulators
Omer Rochman, Gilles Louppe.
https://hdl.handle.net/2268/309361 [PDF]

Dynamic NeRFs for Soccer Scenes
Sacha Lewin, Maxime Vandegar, Thomas Hoyoux, Olivier Barnich, Gilles Louppe.
arXiv:2309.06802 [PDF]

Score-based Data Assimilation
François Rozet, Gilles Louppe.
arXiv:2306.10574 [PDF]

Balancing Simulation-based Inference for Conservative Posteriors
Arnaud Delaunoy, Benjamin Kurt Miller, Patrick Forré, Christoph Weniger, Gilles Louppe.
arXiv:2304.10978 [PDF]

Graph-informed simulation-based inference for models of active matter
Namid R Stillman, Silke Henkes, Roberto Mayor, Gilles Louppe.
arXiv:2304.06806 [PDF]

Neural posterior estimation for exoplanetary atmospheric retrieval
Malavika Vasist, François Rozet, Olivier Absil, Paul Mollière, Evert Nasedkin, Gilles Louppe.
arXiv:2301.06575 [PDF]

Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping
Norman Marlier, Julien Gustin, Olivier Brüls, Gilles Louppe.
arXiv:2304.08805 [PDF]

Policy Gradient Algorithms Implicitly Optimize by Continuation
Adrien Bolland, Gilles Louppe, Damien Ernst.
arXiv:2305.06851 [PDF]

Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks
Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, and Damien Ernst.
arXiv:2106.03228 [PDF]

Cracking the genetic code with neural networks
Marc Joiret, Marine Leclercq, Gaspard Lambrechts, Francesca Rapino, Pierre Close, Gilles Louppe, Liesbet Geris.
doi:10.3389/frai.2023.1128153 [PDF]

2022

Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation
Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe.
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.
arXiv:2110.06581 [PDF]

Adaptive Self-Training for Object Detection
Renaud Vandeghen, Gilles Louppe, Marc Van Droogenbroeck.
arXiv:2212.05911 [PDF]

A deep learning approach for focal-plane wavefront sensing using vortex phase diversity
Maxime Quesnel, Gilles Orban de Xivry, Gilles Louppe, Olivier Absil.
arXiv:2210.00632 [PDF]

Simulation-based Bayesian inference for robotic grasping
Norman Marlier, Olivier Bruls, Gilles Louppe.
openreview.net:q7vnfJK4UBo [PDF]

Bayesian uncertainty quantification for machine-learned models in physics
Yarin Gal, Petros Koumoutsakos, Francois Lanusse, Gilles Louppe, Costas Papadimitriou.
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.
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.
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.
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.
doi:10.1186/s13690-022-00801-w [PDF]

SAE: Sequential Anchored Ensembles
Arnaud Delaunoy, Gilles Louppe.
arXiv:2201.00649 [PDF]

2021

Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference
François Rozet and Gilles Louppe.
arXiv:2110.00449 [PDF]

HNPE: Leveraging Global Parameters for Flow-based Neural Posterior Estimation
Pedro L. C. Rodrigues, Thomas Moreau, Gilles Louppe, and Alexandre Gramfort.
arXiv:2102.06477 [PDF]

Truncated Marginal Neural Ratio Estimation
Benjamin Miller, Alex Cole, Patrick Forré, Gilles Louppe, and Christophe Weniger.
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
arXiv:2111.02218 [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.
arXiv:2011.14923 [PDF]

Simulation-based Bayesian inference for multi-fingered robotic grasping
Norman Marlier, Olivier Bruls, Gilles Louppe.
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.
doi:10.1093/mnras/stab1634 [PDF]

Diffusion Priors In Variational Autoencoders
Antoine Wehenkel and Gilles Louppe.
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.
arXiv:2011.05836 [PDF]

Graphical Normalizing Flows
Antoine Wehenkel and Gilles Louppe
arXiv:2006.02548 [PDF]

Toward Machine Learning Optimization of Experimental Design
Atılım Güneş Baydin et al.
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.
arXiv:2011.13951 [PDF]

Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization
Arnaud Delaunoy et al.
arXiv:2010.12931 [PDF]

Improving the RSM map exoplanet detection algorithm
C.-H. Dahlqvist, Gilles Louppe, Olivier Absil
doi:10.1051/0004-6361/202039597 [PDF]

Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Joeri Hermans, Volodimir Begy, and Gilles Louppe.
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
doi:10.1109/IJCNN48605.2020.9206677 [PDF]

You Say Normalizing Flows I see Bayesian Networks
Antoine Wehenkel and Gilles Louppe
arXiv:2006.00866 [PDF]

The frontier of simulation-based inference
Kyle Cranmer, Johann Brehmer, and Gilles Louppe
doi:10.1073/pnas.1912789117 [PDF]

Mining gold from implicit models to improve likelihood-free inference
Johann Brehmer, Gilles Louppe, Juan Pavez, Kyle Cranmer
doi:10.1073/pnas.1915980117 [PDF]

2019

Machine learning for image-based wavefront sensing
Pierre-Olivier Vanberg, Gilles Orban de Xivry, Olivier Absil, and Gilles Louppe
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
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
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
arXiv:1909.01779 [PDF]

Unconstrained Monotonic Neural Networks
Antoine Wehenkel and Gilles Louppe
arXiv:1908.05164 [PDF]

Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Atılım Güneş Baydin et al.
arXiv:1907.03382 [PDF]

Effective LHC measurements with matrix elements and machine learning
Johann Brehmer, Kyle Cranmer, Irina Espejo, Felix Kling, Gilles Louppe, Juan Pavez
arXiv:1906.01578 [PDF]

Adversarial Variational Optimization of Non-Differentiable Simulators
Gilles Louppe, Kyle Cranmer
arXiv:1707.07113 [PDF]
github:glouppe/paper-avo [code]

2018

Recurrent machines for likelihood-free inference
Arthur Pesah, Antoine Wehenkel and Gilles Louppe.
arXiv:1811.12932 [PDF]

Robust EEG-based cross-site and cross-protocol classification of states of consciousness
Denis Engemann et al.
doi:10.1093/brain/awy251 [PDF]

Deep Quality-Value (DQV) Learning
Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering
arXiv:1810.00368 [PDF]

Likelihood-free inference with an improved cross-entropy estimator
Markus Stoye, Johann Brehmer, Gilles Louppe, Juan Pavez, Kyle Cranmer
arXiv:1808.00973 [PDF]

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
Atilim Gunes Baydin et al.
arXiv:1807.07706 [PDF]

Deep generative models for fast shower simulation in ATLAS
The ATLAS collaboration
https://cds.cern.ch/record/2630433 [PDF]

Machine Learning in High Energy Physics Community White Paper
Kim Albertsson et al.
arXiv:1807.02876 [PDF]

Gradient Energy Matching for Distributed Asynchronous Gradient Descent
Joeri Hermans, Gilles Louppe
arXiv:1805.08469 [PDF]

Constraining Effective Field Theories with Machine Learning
Johann Brehmer, Kyle Cranmer, Gilles Louppe, Juan Pavez
arXiv:1805.00013 [PDF]

A Guide to Constraining Effective Field Theories with Machine Learning
Johann Brehmer, Kyle Cranmer, Gilles Louppe, Juan Pavez
arXiv:1805.00020 [PDF]

2017

Neural Message Passing for Jet Physics
Isaac Henrion, Johann Brehmer, Joan Bruna, Kyunghun Cho, Kyle Cranmer, Gilles Louppe, Gaspar Rochette
https://pdfs.semanticscholar.org/5a85/27a82ec5dee8e645c3e5deea942e79607558.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
arXiv:1712.07901 [PDF]

Random Subspace with Trees for Feature Selection Under Memory Constraints
Antonio Sutera, Célia Chatel, Gilles Louppe, Louis Wehenkel, Pierre Geurts
arXiv:1709.01177 [PDF]

QCD-Aware Recursive Neural Networks for Jet Physics
Gilles Louppe, Kyunghyun Cho, Cyril Becot, Kyle Cranmer
arXiv:1702.00748 [PDF]
github:glouppe/recnn [code]

2016

Random Subspace with Trees for Feature Selection Under Memory Constraints
Antonio Sutera, Célia Chatel, Gilles Louppe, Louis Wehenkel, Pierre Geurts
arXiv:1709.01177 [PDF]

QCD-Aware Recursive Neural Networks for Jet Physics
Gilles Louppe, Kyunghyun Cho, Cyril Becot, Kyle Cranmer
arXiv:1702.00748 [PDF]
github:glouppe/recnn [code]

2015

Approximating Likelihood Ratios with Calibrated Discriminative Classifiers
Kyle Cranmer, Juan Pavez, Gilles Louppe
arXiv:1506.02169 [PDF]

Pitfalls of evaluating a classifier’s performance in high energy physics applications
Gilles Louppe, Tim Head
https://zenodo.org/record/34934 [notebook]

Ethnicity sensitive author disambiguation using semi-supervised learning
Gilles Louppe, Hussein Al-Natsheh, Mateusz Susik, Eamonn Maguire
arXiv:1508.07744 [PDF]
github:glouppe/paper-author-disambiguation [code]

Collaborative analysis of gigapixel images using Cytomine
Rémy Vandaele, Raphaël Marée, Pierre Geurts, Loïc Rollus, Benjamin Stévens, Renaud Hoyoux, Jean-Michel Begon, Gilles Louppe, Louis Wehenkel
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
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
http://hdl.handle.net/2268/177115 [PDF]

2014

Understanding Random Forests
Gilles Louppe
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
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
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
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
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.
http://hdl.handle.net/2268/154357 [PDF]
github:scikit-learn/scikit-learn [code]

2012

Scikit-Learn: Machine Learning in Python
Fabian Pedregosa et al.
arXiv:1201.0490 [PDF]
http://scikit-learn.org/stable/ [website]

Ensembles on Random Patches
Gilles Louppe, Pierre Geurts
http://hdl.handle.net/2268/130099 [PDF]

2011

Learning to rank with extremely randomized trees
Pierre Geurts, Gilles Louppe
http://hdl.handle.net/2268/84538 [PDF]

2010

A zealous parallel gradient descent algorithm
Gilles Louppe, Pierre Geurts
http://hdl.handle.net/2268/80780 [PDF, code]

Collaborative filtering: Scalable approaches using restricted Boltzmann machines
Gilles Louppe
http://hdl.handle.net/2268/74400 [PDF, code]