publications
This page is automatically generated from ORCID data. For the curated version, see publications.
Legend: pre-print conference workshop journal miscellaneous
2026
Exploration of Rationale-Extraction Methods for Closed-Domain Question Answering with a New Sentence-Level Rationale Dataset 
Lize Pirenne, Samy Mokeddem, Damien Ernst, .
Lecture Notes in Computer Science
2025
An implementation of neural simulation-based inference for parameter estimation in ATLAS
Atlas Collaboration, others.
Reports on Progress in Physics
Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation
Gérôme Andry, Sacha Lewin, François Rozet, Omer Rochman, Victor Mangeleer, Matthias Pirlet, Elise Faulx, Marilaure Grégoire, .
pre-print
Contributive Attribution for Question Answering via Tree-based Context Pruning
Lize Pirenne, Gaspard Lambrechts, Norman Marlier, Maxence de la Brassinne Bonardeaux, , Damien Ernst.
journal article
Enforcing governing equation constraints in neural PDE solvers via training-free projections
Omer Rochman, .
pre-print
Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes
Joseph Hoche, Andrei Bursuc, David Brellmann, , Pavel Izmailov, Angela Yao, Gianni Franchi.
pre-print
Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation
François Rozet, Ruben Ohana, Michael McCabe, , François Lanusse, Shirley Ho.
pre-print
Measurement of off-shell Higgs boson production in the H∗→ ZZ→ 4ℓ decay channel using a neural simulation-based inference technique in 13 TeV pp collisions with the ATLAS detector
Atlas Collaboration, others.
Reports on progress in physics
Panchromatic characterization of the Y0 brown dwarf WISEP J173835.52+273258.9 using JWST/MIRI
M. Vasist, P. Mollière, H. Kühnle, P. Patapis, O. Absil, , P.-o. Lagage, L. B. F. M. Waters, M. Güdel, Th. Henning, B. Vandenbussche, D. Barrado, L. Decin, J. P. Pye, P. Tremblin, N. Whiteford.
Astronomy & Astrophysics
Simulation-based inference benchmark for weak lensing cosmology
Justine Zeghal, Denise Lanzieri, François Lanusse, Alexandre Boucaud, , Eric Aubourg, Adrian E. Bayer.
Astronomy & Astrophysics
Training-Free Data Assimilation with GenCast
Thomas Savary, François Rozet, .
pre-print
Turbulent Injection assisted by Diffusion Models for Scale Resolving Simulations
Margaux Boxho, Joachim Dominique, Tariq Benarama, Michel Rasquin, Lionel Salesses, Caroline Sainvitu, , Thomas Toulorge.
pre-print
Turbulent injection assisted by diffusion models for scale-resolving simulations
M. Boxho, J. Dominique, T. Benamara, M. Rasquin, L. Salesses, C. Sainvitu, , T. Toulorge.
Physics of Fluids
2024
A Neural Material Point Method for Particle-based Emulation
Omer Rochman Sharabi, Sacha Lewin, .
pre-print
Characterizing the performance of the SPHERE exoplanet imager at the Very Large Telescope using deep learning
Ludo Bissot, J Milli, E Choquet, F Cantalloube, P Delorme, D Mouillet, , Olivier Absil.
SPIE AO
Cost Estimation in Unit Commitment Problems Using Simulation-Based Inference
Matthias Pirlet, Adrien Bolland, , Damien Ernst.
pre-print
Enhancing phase retrieval with domain adaptation: bridging the gap between simulations and real data
Maxime Quesnel, Gilles Orban de Xivry, Jyotirmay Paul, Olivier Absil, , Vincent Deo, Sébastien Vievard, Olivier Guyon.
SPIE AO
Grasping Under Uncertainties: Sequential Neural Ratio Estimation for 6-DoF Robotic Grasping
Norman Marlier, Olivier Brüls, .
IEEE Robotics and Automation Letters
Harnessing machine learning for accurate treatment of overlapping opacity species in general circulation models
Aaron David Schneider, Paul Mollière, , Ludmila Carone, Uffe Gråe Jørgensen, Leen Decin, Christiane Helling.
Astronomy & Astrophysics
Learning Diffusion Priors from Observations by Expectation Maximization
François Rozet, Gérôme Andry, François Lanusse, .
pre-print
Low-Budget Simulation-Based Inference with Bayesian Neural Networks
Arnaud Delaunoy, Maxence de la Brassinne Bonardeaux, Siddharth Mishra-Sharma, .
pre-print
Neural network-based simulation of fields and losses in electrical machines with ferromagnetic laminated cores
Florent Purnode, François Henrotte, , Christophe Geuzaine.
journal article
Parameter Estimation with Neural Simulation-Based Inference in ATLAS
Rafael Coelho Lopes De Sa, Verena Ingrid Martinez Outschoorn, Aishik Ghosh, Gilles Claude Louppe, Arnaud Jean Maury, David Rousseau, RD Schaffer, Daniel Whiteson, Jay Ajitbhai Sandesara.
miscellaneous
Simulation-Based Inference Benchmark for LSST Weak Lensing Cosmology
Justine Zeghal, Denise Lanzieri, François Lanusse, Alexandre Boucaud, , Eric Aubourg, Adrian E Bayer, Lsst Dark Energy Science Collaboration, others.
pre-print
Video-Driven Graph Network-Based Simulators
Franciszek Szewczyk, , Matthia Sabatelli.
pre-print
2023
Balancing Simulation-based Inference for Conservative Posteriors
Arnaud Delaunoy, Benjamin Kurt Miller, Patrick Forré, Christoph Weniger, .
pre-print
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability
Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, , Alexandros Kalousis.
pre-print
Cracking the genetic code with neural networks
Marc Joiret, Marine Leclercq, Gaspard Lambrechts, Francesca Rapino, Pierre Close, , Liesbet Geris.
Frontiers in Artificial Intelligence
Developing a Video Game as an Awareness and Research Tool Based on SARS-CoV-2 Epidemiological Dynamics and Motivational Perspectives
Alexis Messina, Michael Schyns, Björn-Olav Dozo, Vincent Denoël, Romain Van Hulle, Anne-Marie Etienne, Stéphanie Delroisse, Olivier Bruyère, Vincent D’Orio, Sébastien Fontaine, others.
Transboundary and Emerging Diseases
Distributional reinforcement learning with unconstrained monotonic neural networks
Thibaut Théate, Antoine Wehenkel, Adrien Bolland, , Damien Ernst.
Neurocomputing
Dynamic NeRFs for Soccer Scenes
Sacha Lewin, Maxime Vandegar, Thomas Hoyoux, Olivier Barnich, .
ACM MM
Fast and Accurate Modelling of Laminated Cores in Electrical Machines using Homogenization and Neural Networks
Florent Purnode, François Henrotte, , Christophe Geuzaine.
journal article
Fast and accurate Neural-Network-based Ferromagnetic Laminated Stack Model for Electrical Machine Simulations in Periodic Regime
Florent Purnode, François Henrotte, , Christophe Geuzaine.
COMPUMAG 2023
Graph-informed simulation-based inference for models of active matter
Namid R Stillman, Silke Henkes, Roberto Mayor, .
pre-print
Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping
Norman Marlier, Julien Gustin, , Olivier Brüls.
pre-print
Neural posterior estimation for exoplanetary atmospheric retrieval
Malavika Vasist, François Rozet, Olivier Absil, Paul Mollière, Evert Nasedkin, .
pre-print
Neural-Network-Based Identification of Material Law Parameters for Fast and Accurate Simulations of Electrical Machines in Periodic Regime
Florent Purnode, François Henrotte, , Christophe Geuzaine.
EMF 2023
Policy Gradient Algorithms Implicitly Optimize by Continuation
Adrien Bolland, , Damien Ernst.
pre-print
Robust Ocean Subgrid-Scale Parameterizations Using Fourier Neural Operators
Victor Mangeleer, .
pre-print
Score-based Data Assimilation
François Rozet, .
NeurIPS
Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model
François Rozet, .
pre-print
Trick or treat? Evaluating stability strategies in graph network-based simulators
Omer Rochman Sharabi, .
NeurIPS 2023
2022
A Crisis In Simulation-Based Inference? Beware, Your Posterior Approximations Can Be Unfaithful
Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Volodimir Begy, .
Transactions on Machine Learning Research
A deep learning approach for focal-plane wavefront sensing using vortex phase diversity
Maxime Quesnel, G Orban de Xivry, , Olivier Absil.
pre-print
A Homogenized Material Law based on Neural Networks for the Accurate Prediction of Losses in Electrical Machines
Florent Purnode, François Henrotte, , Christophe Geuzaine.
ACOMEN 2022
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, , Romain Van Hulle, Laurent Gillet, Fabrice Bureau, Vincent Denoël.
Mathematical Biosciences
A Material Law Based on Neural Networks and Homogenization for the Accurate Finite Element Simulation of Laminated Ferromagnetic Cores in the Periodic Regime
Florent Purnode, François Henrotte, François Caire, Joaquim Da Silva, , Christophe Geuzaine.
IEEE Transactions on Magnetics
A physics-based deep learning approach for focal-plane wavefront sensing
Maxime Quesnel, Gilles Orban de Xivry, , Olivier Absil.
SciOps workshop 2022
A simulator-based autoencoder for focal plane wavefront sensing
Maxime Quesnel, Gilles Orban de Xivry, Olivier Absil, .
SPIE AO
Adaptive Self-Training for Object Detection
Renaud Vandeghen, , Marc Van Droogenbroeck.
pre-print
Bayesian uncertainty quantification for machine-learned models in physics
Yarin Gal, Petros Koumoutsakos, Francois Lanusse, , Costas Papadimitriou.
Nature Reviews Physics
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, , Fabrice Bureau, Vincent D’orio, Sébastien Fontaine, Laurent Gillet, Michèle Guillaume, Éric Haubruge, Anne-Catherine Lange, others.
Archives of Public Health
Deep generative models for fast photon shower simulation in ATLAS
Atlas Collaboration, others.
pre-print
Differentiable composition for model discovery
Omer Rochman Sharabi, .
NeurIPS 2022
Improving Generalization with Physical Equations
Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, , Jörn-Henrik Jacobsen.
journal article
Neural Posterior Estimation of hierarchical models in neuroscience
Julia Linhart, Pedro LC Rodrigues, Thomas Moreau, , Alexandre Gramfort.
conference paper
Robust hybrid learning with expert augmentation
Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, , Jörn-Henrik Jacobsen.
pre-print
Simulation-based Bayesian inference for robotic grasping
Norman Marlier, Olivier Brüls, .
PRDL workshop 2022
Springer: Deep Generative Models for Fast Photon Shower Simulation in ATLAS
Georges Aad, Alexander Kupco, Jay Chan, Miguel Angel Principe Martin, Pierre Antoine Delsart, Joey Huston, Yufeng Wang, Karl Jakobs, Martin Spousta, Savanna Shaw, others.
Comput. Softw. Big Sci.
Towards reliable simulation-based inference with balanced neural ratio estimation
Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, .
NeurIPS
2021
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful
Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Volodimir Begy, .
pre-print
Arbitrary marginal neural ratio estimation for simulation-based inference
François Rozet, .
pre-print
Diffusion priors in variational autoencoders
Antoine Wehenkel, .
pre-print
Focal plane wavefront sensing using machine learning: performance of convolutional neural networks compared to fundamental limits
Gilles Orban De Xivry, Maxime Quesnel, PO Vanberg, Olivier Absil, .
Monthly Notices of the Royal Astronomical Society
From global to local mdi variable importances for random forests and when they are shapley values
Antonio Sutera, , Van Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts.
NeurIPS
HNPE: Leveraging global parameters for neural posterior estimation
Pedro Rodrigues, Thomas Moreau, , Alexandre Gramfort.
NeurIPS
Improving the RSM map exoplanet detection algorithm: PSF forward modelling and optimal selection of PSF subtraction techniques
C.-h. Dahlqvist, , O. Absil.
Astronomy and Astrophysics
Leveraging Global Parameters for Flow-based Neural Posterior Estimation
pre-print
SAE: Sequential Anchored Ensembles
Arnaud Delaunoy, .
pre-print
Simulation-based bayesian inference for multi-fingered robotic grasping
Norman Marlier, Olivier Brüls, .
pre-print
Toward machine learning optimization of experimental design
Atılım Güneş Baydin, Kyle Cranmer, Pablo de Castro Manzano, Christophe Delaere, Denis Derkach, Julien Donini, Tommaso Dorigo, Andrea Giammanco, Jan Kieseler, Lukas Layer, others.
Nuclear Physics News
Truncated marginal neural ratio estimation
Benjamin K Miller, Alex Cole, Patrick Forré, , Christoph Weniger.
NeurIPS
2020
Deep learning-based focal plane wavefront sensing for classical and coronagraphic imaging
Maxime Quesnel, Gilles Orban de Xivry, , Olivier Absil.
SPIE AO
Graphical Normalizing Flows
pre-print
Improving the RSM map exoplanet detection algorithm
CH Dahlqvist, , O Absil.
journal article
Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization
pre-print
Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Joeri Hermans, Volodimir Begy, .
ICML
MSL: Mining for Substructure Lenses
Siddharth Mishra-Sharma, Johann Brehmer, .
Astrophysics Source Code Library
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
pre-print
Partially Detected Intelligent Traffic Signal Control using Connectionist Reinforcement Learning
Cyril Geortay, .
journal article
Probing Dark Matter Substructure with Stellar Streams and Neural Simulation-Based Inference
Joeri Hermans, Nilanjan Banik, Christophe Weniger, Gianfranco Bertone, .
NeurIPS workshop
QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning
pre-print
Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time
pre-print
The deep quality-value family of deep reinforcement learning algorithms
Matthia Sabatelli, , Pierre Geurts, Marco A Wiering.
IJCNN 2020
The frontier of simulation-based inference
Kyle Cranmer, Johann Brehmer, .
Proceedings of the National Academy of Sciences
Towards constraining warm dark matter with stellar streams through neural simulation-based inference
pre-print
You say Normalizing Flows I see Bayesian Networks
pre-print
2019
Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms
pre-print
Effective LHC measurements with matrix elements and machine learning
J. Brehmer, K. Cranmer, I. Espejo, F. Kling, , J. Pavez.
Journal of Physics: Conference Series
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Atilim Güneş Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, , Mingfei Ma, Xiaohui Zhao, Philip Torr, Victor Lee, Kyle Cranmer, Prabhat, Frank Wood.
SC
Likelihood-free MCMC with Approximate Likelihood Ratios
pre-print
Machine learning for image-based wavefront sensing
Pierre-Olivier Vanberg, Gilles Orban de Xivry, Olivier Absil, .
NeurIPS workshop 2019
Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning
Johann Brehmer, Siddharth Mishra-Sharma, Joeri Hermans, , Kyle Cranmer.
pre-print
Mining gold: Improving simulation-based inference with latent information
Johann Brehmer, Kyle Cranmer, Siddharth Mishra-Sharma, Felix Kling, .
journal article
Real-time Voice Cloning
Corentin Jemine, .
journal article
Robotic throwing controller for accelerating a recycling line
Norman Marlier, , Olivier Bruls, Godefroid Dislaire.
3rd Robotix-Academy Conference on for Industrials Robotics
Unconstrained Monotonic Neural Networks
pre-print
2018
A guide to constraining effective field theories with machine learning
Johann Brehmer, Kyle Cranmer, , Juan Pavez.
Physical Review D
Apprentissage par renforcement en vue de l’amélioration d’une ligne de recyclage robotisée
Norman Marlier, others.
journal article
Constraining effective field theories with machine learning
Johann Brehmer, Kyle Cranmer, , Juan Pavez.
Physical review letters
Deep generative models for fast shower simulation in ATLAS
Kyle Cranmer, Stefan Gadatsch, Aishik Ghosh, Tobias Golling, , David Rousseau, Dalila Salamani, Graeme Stewart.
journal article
Deep quality-value (DQV) learning
pre-print
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
pre-print
Gradient energy matching for distributed asynchronous gradient descent
Joeri Hermans, .
pre-print
Levelset estimation by Bayesian optimization
K Cranmer, L Heinrich, .
miscellaneous
Likelihood-free inference with an improved cross-entropy estimator
Markus Stoye, Johann Brehmer, , Juan Pavez, Kyle Cranmer.
pre-print
Machine learning in high energy physics community white paper
Kim Albertsson, Piero Altoe, Dustin Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano, Laurent Basara, Adrian Bevan, Wahid Bhimji, Daniele Bonacorsi, Paolo Calafiura, Mario Campanelli, Louis Capps, Federico Carminati, Stefano Carrazza, Taylor Childers, Elias Coniavitis, Kyle Cranmer, Claire David, Douglas Davis, Javier Duarte, Martin Erdmann, Jonas Eschle, Amir Farbin, Matthew Feickert, Nuno Filipe Castro, Conor Fitzpatrick, Michele Floris, Alessandra Forti, Jordi Garra-Tico, Jochen Gemmler, Maria Girone, Paul Glaysher, Sergei Gleyzer, Vladimir Gligorov, Tobias Golling, Jonas Graw, Lindsey Gray, Dick Greenwood, Thomas Hacker, John Harvey, Benedikt Hegner, Lukas Heinrich, Ben Hooberman, Johannes Junggeburth, Michael Kagan, Meghan Kane, Konstantin Kanishchev, Przemysław Karpiński, Zahari Kassabov, Gaurav Kaul, Dorian Kcira, Thomas Keck, Alexei Klimentov, Jim Kowalkowski, Luke Kreczko, Alexander Kurepin, Rob Kutschke, Valentin Kuznetsov, Nicolas Köhler, Igor Lakomov, Kevin Lannon, Mario Lassnig, Antonio Limosani, , Aashrita Mangu, Pere Mato, Helge Meinhard, Dario Menasce, Lorenzo Moneta, Seth Moortgat, Meenakshi Narain, Mark Neubauer, Harvey Newman, Hans Pabst, Michela Paganini, Manfred Paulini, Gabriel Perdue, Uzziel Perez, Attilio Picazio, Jim Pivarski, Harrison Prosper, Fernanda Psihas, Alexander Radovic, Ryan Reece, Aurelius Rinkevicius, Eduardo Rodrigues, Jamal Rorie, David Rousseau, Aaron Sauers, Steven Schramm, Ariel Schwartzman, Horst Severini, Paul Seyfert, Filip Siroky, Konstantin Skazytkin, Mike Sokoloff, Graeme Stewart, Bob Stienen, Ian Stockdale, Giles Strong, Savannah Thais, Karen Tomko, Eli Upfal, Emanuele Usai, Andrey Ustyuzhanin, Martin Vala, Sofia Vallecorsa, Justin Vasel, Mauro Verzetti, Xavier Vilasís-Cardona, Jean-Roch Vlimant, Ilija Vukotic, Sean-Jiun Wang, Gordon Watts, Michael Williams, Wenjing Wu, Stefan Wunsch, Omar Zapata.
Journal of Physics: Conference Series
Mining gold from implicit models to improve likelihood-free inference
Johann Brehmer, , Juan Pavez, Kyle Cranmer.
Proceedings of the National Academy of Sciences
New approaches using machine learning for fast shower simulation in ATLAS
Ahmed Hasib, Tobias Golling, Aishik Ghosh, Dalila Salamani, David Rousseau, Kyle Cranmer, Gilles Claude Louppe, Graeme Stewart, Jana Schaarschmidt, Stefan Gadatsch.
miscellaneous
Recurrent machines for likelihood-free inference
Arthur Pesah, Antoine Wehenkel, .
pre-print
Robust EEG-based cross-site and cross-protocol classification of states of consciousness
Denis A Engemann, Federico Raimondo, Jean-Rémi King, Benjamin Rohaut, , Frédéric Faugeras, Jitka Annen, Helena Cassol, Olivia Gosseries, Diego Fernandez-Slezak, Steven Laureys, Lionel Naccache, Stanislas Dehaene, Jacobo D Sitt.
Brain
scikit-optimize/scikit-optimize
Tim Head, MechCoder, , Iaroslav Shcherbatyi.
miscellaneous
2017
Adversarial variational optimization of non-differentiable simulators
pre-print
Improvements to inference compilation for probabilistic programming in large-scale scientific simulators
Mario Lezcano Casado, Atilim Gunes Baydin, David Mart́ınez Rubio, Tuan Anh Le, Frank Wood, Lukas Heinrich, , Kyle Cranmer, Karen Ng, Wahid Bhimji, others.
pre-print
Neural Message Passing for Jet Physics
Isaac Henrion, Johann Brehmer, Joan Bruna, Kyunghun Cho, Kyle Cranmer, , Gaspar Rochette.
journal article
QCD-Aware Recursive Neural Networks for Jet Physics
, Kyunghyun Cho, Cyril Becot, Kyle Cranmer.
Journal of High Energy Physics
Random subspace with trees for feature selection under memory constraints
pre-print
2016
Approximating Likelihood Ratios with Calibrated Discriminative Classifiers
Kyle Cranmer, Juan Pavez, .
pre-print
carl: a likelihood-free inference toolbox
, Kyle Cranmer, Juan Pavez.
The Journal of Open Source Software
Clusterix: a visual analytics approach to clustering
E Maguire, I Koutsakis, .
IEEE VIS
Collaborative analysis of multi-gigapixel imaging data using Cytomine
Raphaël Marée, Loïc Rollus, Benjamin Stévens, Renaud Hoyoux, , Rémy Vandaele, Jean-Michel Begon, Philipp Kainz, Pierre Geurts, Louis Wehenkel.
Bioinformatics
Context-dependent feature analysis with random forests
pre-print
Cytomine: An open-source software for collaborative analysis of whole-slide images
R Marée, L Rollus, B Stévens, R Hoyoux, , R Vandaele, J-m Begon, P Kainz, P Geurts, L Wehenkel.
Diagnostic Pathology
Experiments using machine learning to approximate likelihood ratios for mixture models
K Cranmer, J Pavez, , W K Brooks.
Journal of Physics: Conference Series
Learning to Pivot with Adversarial Networks
pre-print
Unifying generative models and exact likelihood-free inference with conditional bijections
Kyle Cranmer, .
doi:10.5281/zenodo.198541
Visualization of Publication Impact
Eamonn Maguire, Javier Martin Montull, .
pre-print
2015
Ethnicity sensitive author disambiguation using semi-supervised learning
, Hussein T. Al-Natsheh, Mateusz Susik, Eamonn James Maguire.
Communications in Computer and Information Science
Pitfalls of evaluating a classifier’s performance in high energy physics applications
, Tim Head.
doi:10.5281/zenodo.34934
Scikit-learn: Machine learning without learning the machinery
Gaël Varoquaux, Lars Buitinck, , Olivier Grisel, Fabian Pedregosa, Andreas Mueller.
GetMobile: Mobile Computing and Communications
Simple connectome inference from partial correlation statistics in calcium imaging
Antonio Sutera, Arnaud Joly, Vincent François-Lavet, Aaron Qiu, , Damien Ernst, Pierre Geurts.
Neural Connectomics workshop
2014
A hybrid human-computer approach for large-scale image-based measurements using web services and machine learning
Raphaël Marée, Löıc Rollus, Benjamin Stévens, , Olivier Caubo, Natacha Rocks, Sandrine Bekaert, Didier Cataldo, Louis Wehenkel.
ISBI 2014
Exploiting SNP correlations within random forest for genome-wide association studies
Vincent Botta, , Pierre Geurts, Louis Wehenkel.
PloS one
Forecasting daily solar energy production using robust regression techniques
, Peter Prettenhofer.
AMS
Gradient boosted regression trees in scikit-learn
Peter Prettenhofer, .
PyData 2014
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, , Peter Prettenhofer, Jeffrey Basara, Thomas Hamill, others.
journal article
Understanding Random Forests: From Theory to Practice
.
Unpublished
2013
API design for machine learning software: experiences from the scikit-learn project
Lars Buitinck, , Mathieu Blondel, Fabian Pedregosa, Andreas Mueller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Alexandre Gramfort, Jaques Grobler, others.
pre-print
Understanding variable importances in forests of randomized trees
NeurIPS
2012
A rich internet application for remote visualization, collaborative annotation, and automated analysis of large-scale biomages
Raphaël Marée, Benjamin Stevens, Löıc Rollus, , Louis Wehenkel.
Turning Images to Knowledge: Large-Scale 3D Image Annotation, Management, and Visualization
Ensembles on random patches
, Pierre Geurts.
ECML-PKDD 2012
Scikit-learn: Machine learning in Python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Andreas Müller, Joel Nothman, , others.
pre-print
2011
Learning to rank with extremely randomized trees
JMLR: Workshop and Conference Proceedings
2010
A zealous parallel gradient descent algorithm
, Pierre Geurts.
NeurIPS workshop 2010
Collaborative filtering: Scalable approaches using restricted Boltzmann machines
.
miscellaneous