Gilles Louppe - RankMe

104 papers A* 10A 6B 1Journal 70Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Predict-Project-Renoise: Sampling Diffusion Models under Hard Constraints. CoRR Omer Rochman Sharabi, Gilles Louppe
2025	J	`jnl`	A Neural Material Point Method for Particle-based Emulation. Trans. Mach. Learn. Res. Omer Rochman Sharabi, Sacha Lewin, Gilles Louppe
2025	J	`jnl`	Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation. CoRR Gérôme Andry, François Rozet, Sacha Lewin, Omer Rochman Sharabi, Victor Mangeleer, Matthias Pirlet, Elise Faulx, Marilaure Grégoire, Gilles Louppe
2025	J	`jnl`	Enforcing governing equation constraints in neural PDE solvers via training-free projections. CoRR Omer Rochman, Gilles Louppe
2025	—	`conf`	Exploration of Rationale-Extraction Methods for Closed-Domain Question Answering with a New Sentence-Level Rationale Dataset. NLDB (2) Lize Pirenne, Samy Mokeddem, Damien Ernst, Gilles Louppe
2025	J	`jnl`	Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes. CoRR Joseph Hoche, Andrei Bursuc, David Brellmann, Gilles Louppe, Pavel Izmailov, Angela Yao, Gianni Franchi
2025	J	`jnl`	Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation. CoRR François Rozet, Ruben Ohana, Michael McCabe, Gilles Louppe, François Lanusse, Shirley Ho
2025	J	`jnl`	Training-Free Data Assimilation with GenCast. CoRR Thomas Savary, François Rozet, Gilles Louppe
2024	J	`jnl`	A Neural Material Point Method for Particle-based Simulations. CoRR Omer Rochman Sharabi, Sacha Lewin, Gilles Louppe
2024	J	`jnl`	Costs Estimation in Unit Commitment Problems using Simulation-Based Inference. CoRR Matthias Pirlet, Adrien Bolland, Gilles Louppe, Damien Ernst
2024	J	`jnl`	Grasping Under Uncertainties: Sequential Neural Ratio Estimation for 6-DoF Robotic Grasping. IEEE Robotics Autom. Lett. Norman Marlier, Olivier Brüls, Gilles Louppe
2024	A*	`conf`	Learning Diffusion Priors from Observations by Expectation Maximization. NeurIPS François Rozet, Gérôme Andry, François Lanusse, Gilles Louppe
2024	J	`jnl`	Learning Diffusion Priors from Observations by Expectation Maximization. CoRR François Rozet, Gérôme Andry, François Lanusse, Gilles Louppe
2024	J	`jnl`	Low-Budget Simulation-Based Inference with Bayesian Neural Networks. CoRR Arnaud Delaunoy, Maxence de la Brassinne Bonardeaux, Siddharth Mishra-Sharma, Gilles Louppe
2024	J	`jnl`	Video-Driven Graph Network-Based Simulators. CoRR Franciszek Szewczyk, Gilles Louppe, Matthia Sabatelli
2023	—	`conf`	Adaptive Self-Training for Object Detection. ICCV (Workshops) Renaud Vandeghen, Gilles Louppe, Marc Van Droogenbroeck
2023	J	`jnl`	Balancing Simulation-based Inference for Conservative Posteriors. CoRR Arnaud Delaunoy, Benjamin Kurt Miller, Patrick Forré, Christoph Weniger, Gilles Louppe
2023	A*	`conf`	Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. NeurIPS Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis
2023	J	`jnl`	Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. CoRR Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis
2023	J	`jnl`	Cracking the genetic code with neural networks. Frontiers Artif. Intell. Marc Joiret, Marine Leclercq, Gaspard Lambrechts, Francesca Rapino, Pierre Close, Gilles Louppe, Liesbet Geris
2023	J	`jnl`	Distributional reinforcement learning with unconstrained monotonic neural networks. Neurocomputing Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, Damien Ernst
2023	—	`conf`	Dynamic NeRFs for Soccer Scenes. MMSports@MM Sacha Lewin, Maxime Vandegar, Thomas Hoyoux, Olivier Barnich, Gilles Louppe
2023	J	`jnl`	Dynamic NeRFs for Soccer Scenes. CoRR Sacha Lewin, Maxime Vandegar, Thomas Hoyoux, Olivier Barnich, Gilles Louppe
2023	J	`jnl`	Graph-informed simulation-based inference for models of active matter. CoRR Namid R. Stillman, Silke Henkes, Roberto Mayor, Gilles Louppe
2023	J	`jnl`	Harnessing machine learning for accurate treatment of overlapping opacity species in GCMs. CoRR Aaron David Schneider, Paul Mollière, Gilles Louppe, Ludmila Carone, Uffe Gråe Jørgensen, Leen Decin, Christiane Helling
2023	J	`jnl`	Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping. CoRR Norman Marlier, Julien Gustin, Olivier Brüls, Gilles Louppe
2023	J	`jnl`	Policy Gradient Algorithms Implicitly Optimize by Continuation. CoRR Adrien Bolland, Gilles Louppe, Damien Ernst
2023	J	`jnl`	Policy Gradient Algorithms Implicitly Optimize by Continuation. Trans. Mach. Learn. Res. Adrien Bolland, Gilles Louppe, Damien Ernst
2023	J	`jnl`	Robust Hybrid Learning With Expert Augmentation. Trans. Mach. Learn. Res. Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Jörn-Henrik Jacobsen
2023	J	`jnl`	Robust Ocean Subgrid-Scale Parameterizations Using Fourier Neural Operators. CoRR Victor Mangeleer, Gilles Louppe
2023	J	`jnl`	Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model. CoRR François Rozet, Gilles Louppe
2023	A*	`conf`	Score-based Data Assimilation. NeurIPS François Rozet, Gilles Louppe
2023	J	`jnl`	Score-based Data Assimilation. CoRR François Rozet, Gilles Louppe
2023	J	`jnl`	Simulation-based Bayesian inference for robotic grasping. CoRR Norman Marlier, Olivier Brüls, Gilles Louppe
2022	J	`jnl`	A Crisis In Simulation-Based Inference? Beware, Your Posterior Approximations Can Be Unfaithful. Trans. Mach. Learn. Res. Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Volodimir Begy, Gilles Louppe
2022	J	`jnl`	Adaptive Self-Training for Object Detection. CoRR Renaud Vandeghen, Gilles Louppe, Marc Van Droogenbroeck
2022	J	`jnl`	Robust Hybrid Learning With Expert Augmentation. CoRR Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Jörn-Henrik Jacobsen
2022	J	`jnl`	SAE: Sequential Anchored Ensembles. CoRR Arnaud Delaunoy, Gilles Louppe
2022	A*	`conf`	Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation. NeurIPS Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe
2022	J	`jnl`	Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation. CoRR Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe
2021	J	`jnl`	Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference. CoRR François Rozet, Gilles Louppe
2021	J	`jnl`	Averting A Crisis In Simulation-Based Inference. CoRR Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Gilles Louppe
2021	J	`jnl`	Diffusion Priors In Variational Autoencoders. CoRR Antoine Wehenkel, Gilles Louppe
2021	J	`jnl`	Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks. CoRR Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, Damien Ernst
2021	A*	`conf`	From global to local MDI variable importances for random forests and when they are Shapley values. NeurIPS Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
2021	J	`jnl`	From global to local MDI variable importances for random forests and when they are Shapley values. CoRR Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
2021	A	`conf`	Graphical Normalizing Flows. AISTATS Antoine Wehenkel, Gilles Louppe
2021	A*	`conf`	HNPE: Leveraging Global Parameters for Neural Posterior Estimation. NeurIPS Pedro Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort
2021	J	`jnl`	Leveraging Global Parameters for Flow-based Neural Posterior Estimation. CoRR Pedro L. C. Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort
2021	A	`conf`	Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference. AISTATS Maxime Vandegar, Michael Kagan, Antoine Wehenkel, Gilles Louppe
2021	J	`jnl`	Simulation-based Bayesian inference for multi-fingered robotic grasping. CoRR Norman Marlier, Olivier Brüls, Gilles Louppe
2021	A*	`conf`	Truncated Marginal Neural Ratio Estimation. NeurIPS Benjamin Kurt Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger
2021	J	`jnl`	Truncated Marginal Neural Ratio Estimation. CoRR Benjamin Kurt Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger
2020	—	`ed.`	Artificial Intelligence and Machine Learning - 31st Benelux AI Conference, BNAIC 2019, and 28th Belgian-Dutch Machine Learning Conference, BENELEARN 2019, Brussels, Belgium, November 6-8, 2019, Revised Selected Papers BNAIC/BENELEARN (Selected Papers) Bart Bogaerts, Gianluca Bontempi, Pierre Geurts, Nick Harley, Bertrand Lebichot, Tom Lenaerts, Gilles Louppe
2020	J	`jnl`	Graphical Normalizing Flows. CoRR Antoine Wehenkel, Gilles Louppe
2020	J	`jnl`	Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization. CoRR Arnaud Delaunoy, Antoine Wehenkel, Tanja Hinderer, Samaya Nissanke, Christoph Weniger, Andrew R. Williamson, Gilles Louppe
2020	A*	`conf`	Likelihood-free MCMC with Amortized Approximate Ratio Estimators. ICML Joeri Hermans, Volodimir Begy, Gilles Louppe
2020	J	`jnl`	Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference. CoRR Maxime Vandegar, Michael Kagan, Antoine Wehenkel, Gilles Louppe
2020	J	`jnl`	QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning. CoRR Pascal Leroy, Damien Ernst, Pierre Geurts, Gilles Louppe, Jonathan Pisane, Matthia Sabatelli
2020	J	`jnl`	Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time. CoRR Benjamin Kurt Miller, Alex Cole, Gilles Louppe, Christoph Weniger
2020	B	`conf`	The Deep Quality-Value Family of Deep Reinforcement Learning Algorithms. IJCNN Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering
2020	J	`jnl`	You say Normalizing Flows I see Bayesian Networks. CoRR Antoine Wehenkel, Gilles Louppe
2019	A	`conf`	Adversarial Variational Optimization of Non-Differentiable Simulators. AISTATS Gilles Louppe, Joeri Hermans, Kyle Cranmer
2019	—	`conf`	Adversarial Variational Optimization of Non-Differentiable Simulators. BNAIC/BENELEARN Gilles Louppe, Joeri Hermans, Kyle Cranmer
2019	J	`jnl`	Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms. CoRR Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering
2019	—	`conf`	Deep Quality-Value (DQV) Learning. BNAIC/BENELEARN Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering
2019	A*	`conf`	Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. NeurIPS Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley Gram-Hansen, Gilles Louppe, Lawrence Meadows, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
2019	J	`jnl`	Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale. CoRR Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
2019	A	`conf`	Etalumis: bringing probabilistic programming to scientific simulators at scale. SC Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
2019	J	`jnl`	Likelihood-free MCMC with Approximate Likelihood Ratios. CoRR Joeri Hermans, Volodimir Begy, Gilles Louppe
2019	—	`ed.`	Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), Brussels, Belgium, November 6-8, 2019. BNAIC/BENELEARN Katrien Beuls, Bart Bogaerts, Gianluca Bontempi, Pierre Geurts, Nick Harley, Bertrand Lebichot, Tom Lenaerts, Gilles Louppe, Paul Van Eecke
2019	J	`jnl`	The frontier of simulation-based inference. CoRR Kyle Cranmer, Johann Brehmer, Gilles Louppe
2019	—	`conf`	Unconstrained Monotonic Neural Networks. BNAIC/BENELEARN Antoine Wehenkel, Gilles Louppe
2019	A*	`conf`	Unconstrained Monotonic Neural Networks. NeurIPS Antoine Wehenkel, Gilles Louppe
2019	J	`jnl`	Unconstrained Monotonic Neural Networks. CoRR Antoine Wehenkel, Gilles Louppe
2018	J	`jnl`	Deep Quality-Value (DQV) Learning. CoRR Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering
2018	J	`jnl`	Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. CoRR Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen, Gilles Louppe, Lei Shao, Prabhat, Kyle Cranmer, Frank D. Wood
2018	J	`jnl`	Gradient Energy Matching for Distributed Asynchronous Gradient Descent. CoRR Joeri Hermans, Gilles Louppe
2018	J	`jnl`	Likelihood-free inference with an improved cross-entropy estimator. CoRR Markus Stoye, Johann Brehmer, Gilles Louppe, Juan Pavez, Kyle Cranmer
2018	J	`jnl`	Mining gold from implicit models to improve likelihood-free inference. CoRR Johann Brehmer, Gilles Louppe, Juan Pavez, Kyle Cranmer
2018	A	`conf`	Random Subspace with Trees for Feature Selection Under Memory Constraints. AISTATS Antonio Sutera, Célia Châtel, Gilles Louppe, Louis Wehenkel, Pierre Geurts
2018	J	`jnl`	Recurrent machines for likelihood-free inference. CoRR Arthur Pesah, Antoine Wehenkel, Gilles Louppe
2017	J	`jnl`	Adversarial Variational Optimization of Non-Differentiable Simulators. CoRR Gilles Louppe, Kyle Cranmer
2017	J	`jnl`	Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators. CoRR Mario Lezcano Casado, Atilim Gunes Baydin, David Martínez-Rubio, Tuan Anh Le, Frank D. Wood, Lukas Heinrich, Gilles Louppe, Kyle Cranmer, Karen Ng, Wahid Bhimji, Prabhat
2017	—	`conf`	Learning to Pivot with Adversarial Networks. NIPS Gilles Louppe, Michael Kagan, Kyle Cranmer
2017	J	`jnl`	Random Subspace with Trees for Feature Selection Under Memory Constraints. CoRR Antonio Sutera, Célia Châtel, Gilles Louppe, Louis Wehenkel, Pierre Geurts
2016	J	`jnl`	Collaborative analysis of multi-gigapixel imaging data using Cytomine. Bioinform. Raphaël Marée, Loic Rollus, Benjamin Stevens, Renaud Hoyoux, Gilles Louppe, Remy Vandaele, Jean-Michel Begon, Philipp Kainz, Pierre Geurts, Louis Wehenkel
2016	A	`conf`	Context-dependent feature analysis with random forests. UAI Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
2016	J	`jnl`	Context-dependent feature analysis with random forests. CoRR Antonio Sutera, Gilles Louppe, Vân Anh Huynh-Thu, Louis Wehenkel, Pierre Geurts
2016	—	`conf`	Ethnicity Sensitive Author Disambiguation Using Semi-supervised Learning. KESW Gilles Louppe, Hussein T. Al-Natsheh, Mateusz Susik, Eamonn James Maguire
2016	J	`jnl`	Learning to Pivot with Adversarial Networks. CoRR Gilles Louppe, Michael Kagan, Kyle Cranmer
2016	—	`conf`	Visualization of Publication Impact. EuroVis (Short Papers) Eamonn Maguire, Javier Martin Montull, Gilles Louppe
2016	J	`jnl`	Visualization of Publication Impact. CoRR Eamonn James Maguire, Javier Martin Montull, Gilles Louppe
2016	J	`jnl`	carl: a likelihood-free inference toolbox. J. Open Source Softw. Gilles Louppe, Kyle Cranmer, Juan Pavez
2015	J	`jnl`	Ethnicity sensitive author disambiguation using semi-supervised learning. CoRR Gilles Louppe, Hussein T. Al-Natsheh, Mateusz Susik, Eamonn James Maguire
2015	J	`jnl`	Scikit-learn: Machine Learning Without Learning the Machinery. GetMobile Mob. Comput. Commun. Gaël Varoquaux, Lars Buitinck, Gilles Louppe, Olivier Grisel, Fabian Pedregosa, Andreas Mueller
2014	—	`conf`	A hybrid human-computer approach for large-scale image-based measurements using web services and machine learning. ISBI Raphaël Marée, Loic Rollus, Benjamin Stevens, Gilles Louppe, Olivier Caubo, Natacha Rocks, Sandrine Bekaert, Didier Cataldo, Louis Wehenkel
2014	—	`conf`	Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging. Neural Connectomics Antonio Sutera, Arnaud Joly, Vincent François-Lavet, Zixiao Aaron Qiu, Gilles Louppe, Damien Ernst, Pierre Geurts
2014	J	`jnl`	Simple connectome inference from partial correlation statistics in calcium imaging. CoRR Antonio Sutera, Arnaud Joly, Vincent François-Lavet, Zixiao Aaron Qiu, Gilles Louppe, Damien Ernst, Pierre Geurts
2014	—	`—`	Understanding Random Forests: From Theory to Practice. Gilles Louppe
2013	J	`jnl`	API design for machine learning software: experiences from the scikit-learn project. CoRR Lars Buitinck, Gilles Louppe, Mathieu Blondel, Fabian Pedregosa, Andreas Mueller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Alexandre Gramfort, Jaques Grobler, Robert Layton, Jake VanderPlas, Arnaud Joly, Brian Holt, Gaël Varoquaux
2013	—	`conf`	Understanding variable importances in forests of randomized trees. NIPS Gilles Louppe, Louis Wehenkel, Antonio Sutera, Pierre Geurts
2012	—	`conf`	Ensembles on Random Patches. ECML/PKDD (1) Gilles Louppe, Pierre Geurts
2011	—	`conf`	Learning to rank with extremely randomized trees. Yahoo! Learning to Rank Challenge Pierre Geurts, Gilles Louppe