Louppe, Gilles

The frontier of simulation-based inference

Cranmer, K., Brehmer, J., & Louppe, G. (2020) · Proceedings of the National Academy of Sciences

Markov Chains and Monte Carlo MethodsSimulation Techniques and Applications

Cited by 1,032

Understanding Random Forests: From Theory to Practice

Louppe, G. (2014) · arXiv

Statistical Methods and InferenceData Mining Algorithms and Applications

Cited by 693

Robust EEG-based cross-site and cross-protocol classification of states of consciousness

Engemann, D. A., Raimondo, F., King, J.-R., Rohaut, B., Louppe, G., Faugeras, F., Annen, J., Cassol, H., Gosseries, O., Fernandez-Slezak, D., et al. (2018) · Brain

EEG and Brain-Computer InterfacesTraumatic Brain Injury Research

Cited by 329

scikit-optimize/scikit-optimize

Head, T., Kumar, M., Nahrstaedt, H., Louppe, G., & Shcherbatyi, I. (2021) · Zenodo

Advanced Bandit Algorithms ResearchAdvanced Multi-Objective Optimization Algorithms

Cited by 302

Mining for Dark Matter Substructure: Inferring Subhalo Population Properties from Strong Lenses with Machine Learning

Brehmer, J., Mishra-Sharma, S., Hermans, J., Louppe, G., & Cranmer, K. (2019) · The Astrophysical Journal

Galaxies: Formation, Evolution, PhenomenaDark Matter and Cosmic Phenomena

Cited by 80