Gilles Louppe
- API design for machine learning software: experiences from the scikit-learn project
2013/09/01 by Lars Buitinck, Gilles Louppe, Mathieu Blondel +12 · 3 voices · 13 citations
Computer Science · #cs.LG #cs.MS
- Mining gold from implicit models to improve likelihood-free inference
2018/05/30 by Johann Brehmer, Gilles Louppe, Juan Pavez +2 · 1 voice · 12 citations
Computer Science · Engineering · Mathematics · Physics and Astronomy · #Fault Detection and Control Systems #Machine Learning and Algorithms #Mineral Processing and Grinding #cs.LG #hep-ph #physics.data-an #stat.ML
- Approximating Likelihood Ratios with Calibrated Discriminative Classifiers
2015/06/06 by K. Cranmer, Cranmer, Kyle, Juan Pavez +3 · 36 citations
Computer Science · #Gaussian Processes and Bayesian Inference #Algorithms and Data Compression #Bayesian Methods and Mixture Models
- Score-based Data Assimilation
2023/06/18 by François Rozet, Gilles Louppe, Rozet, François +1 · 1 voice · 19 citations
Computer Science · Physics and Astronomy · #Gaussian Processes and Bayesian Inference #Statistical Mechanics and Entropy #Generative Adversarial Networks and Image Synthesis
- Machine Learning in High Energy Physics Community White Paper
2018/07/08 by Kim Albertsson, Piero Altoè, Albertsson, Kim +224 · 10 citations
Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neutrino Physics Research #Particle Detector Development and Performance #Particle physics theoretical and experimental studies
- QCD-Aware Recursive Neural Networks for Jet Physics
2017/02/02 by Gilles Louppe, Kyunghyun Cho, Cyril Becot +1 · 1 voice · 5 citations
#hep-ph #physics.data-an #stat.ML
- A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful
2021/10/13 by Joeri Hermans, Arnaud Delaunoy, Hermans, Joeri +9 · 6 citations
Computer Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
- Graphical Normalizing Flows
2020/06/03 by Antoine Wehenkel, Wehenkel, Antoine, Gilles Louppe +1 · 6 citations
Computer Science · #Bayesian Modeling and Causal Inference #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare
- Likelihood-free inference with an improved cross-entropy estimator
2018/08/02 by Markus Stoye, Johann Brehmer, Stoye, Markus +7 · 6 citations
Computer Science · Mathematics · #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Markov Chains and Monte Carlo Methods
- Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
2020/11/11 by Maxime Vandegar, M. Kagan, Vandegar, Maxime +5 · 5 citations
Computer Science · Engineering · Physics and Astronomy · #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Gaussian Processes and Bayesian Inference #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Nuclear reactor physics and engineering #Statistics and Probability (physics.data-an)
- Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
2019/07/08 by Atılım Güneş Baydin, Lei Shao, Wahid Bhimji +14 · 1 voice · 1 citation
Computer Science · Mathematics · #cs.LG #cs.PF #stat.ML
- Diffusion Priors In Variational Autoencoders
2021/06/29 by Antoine Wehenkel, Wehenkel, Antoine, Gilles Louppe +1 · 3 citations
Computer Science · Physics and Astronomy · #Generative Adversarial Networks and Image Synthesis #Model Reduction and Neural Networks #Machine Learning in Healthcare
- HNPE: Leveraging Global Parameters for Neural Posterior Estimation
2021/02/12 by Pedro Luiz Coelho Rodrigues, Rodrigues, Pedro L. C., Thomas Moreau +5 · 3 citations
Computer Science · Neuroscience · #Blind Source Separation Techniques #FOS: Biological sciences #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural dynamics and brain function #Quantitative Methods (q-bio.QM)
- Simulation-Based Inference Benchmark for Weak Lensing Cosmology
2024/09/26 by Justine Zeghal, Denise Lanzieri, Zeghal, Justine +12 · 5 citations
Engineering · Physics and Astronomy · #Adaptive optics and wavefront sensing #Astronomical Observations and Instrumentation #Astronomy and Astrophysical Research #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM)
- Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model
2023/10/03 by François Rozet, Rozet, François, Gilles Louppe +1 · 3 citations
Earth and Planetary Sciences · Economics, Econometrics and Finance · Environmental Science · #Atmospheric and Oceanic Physics (physics.ao-ph) #Climate variability and models #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Meteorological Phenomena and Simulations
- Arbitrary Marginal Neural Ratio Estimation for Simulation-based\n Inference
2021/10/01 by François Rozet, Gilles Louppe, Rozet, François +1 · 2 citations
Earth and Planetary Sciences · Engineering · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Pulsars and Gravitational Waves Research #Reservoir Engineering and Simulation Methods #Seismic Imaging and Inversion Techniques #Statistical and numerical algorithms
- Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation
2025/04/25 by Gérôme Andry, Sacha Lewin, Andry, Gérôme +15 · 2 voices · 6 citations
Earth and Planetary Sciences · Environmental Science · Physics and Astronomy · #Climate variability and models #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks #cs.LG #physics.ao-ph
- A Neural Material Point Method for Particle-based Emulation
2024/08/28 by Omer Rochman Sharabi, Sharabi, Omer Rochman, S. Z. Lewin +4 · 1 voice · 2 citations
Engineering · #Fluid Dynamics Simulations and Interactions #Lattice Boltzmann Simulation Studies #cs.LG
- Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time
2020/11/27 by B. Miller, Miller, Benjamin Kurt, Alex Cole +5 · 1 citation
Computer Science · Medicine · Physics and Astronomy · #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Computer and information sciences #FOS: Physical sciences #Gaussian Processes and Bayesian Inference #High Energy Physics - Phenomenology (hep-ph) #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Machine Learning (cs.LG) #Medical Imaging Techniques and Applications #Model Reduction and Neural Networks
- Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation
2025/07/03 by François Rozet, Rozet, François, Ruben Ohana +10 · 1 voice · 6 citations
Computer Science · Decision Sciences · #Advanced Text Analysis Techniques #Scientific Computing and Data Management #Topic Modeling #cs.LG #physics.flu-dyn
- Likelihood-free MCMC with Amortized Approximate Ratio Estimators
2019/03/10 by Joeri Hermans, Hermans, Joeri, Volodimir Begy +3 · 1 citation
Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Model Reduction and Neural Networks
- An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learning
2026/07/23 by Maximilian Dax, Theo Heimel, Gilles Louppe · 1 voice
#cs.LG #astro-ph.CO #astro-ph.GA #hep-ex #hep-ph #stat.ML
- Accounting for Hysteresis and Eddy Currents in Finite Element Simulations of Ferromagnetic Laminated Cores using a Recurrent Neural Network
2026/07/15 by Florent Purnode, Louis Denis, François Henrotte +2
#cs.CE #cs.AI #cs.NA #math.NA