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Location:Paris
Home Page:https://edgarjaber.github.io
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Flexible and efficient tools for high-dimensional approximation, scientific machine learning and uncertainty quantification.
Learning the optimal transport map via input convex neural neworks
Fast Gaussian-process inference using Vecchia approximations
Monotone Parameterization Toolkit (MParT): A core library for constructing and using transport maps.
Large-scale, multi-GPU capable, kernel solver
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
