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cs.LG2025
Reframing Generative Models for Physical Systems using Stochastic Interpolants
Anthony Zhou, Alexander Wikner, Amaury Lancelin +2
Generative models have recently emerged as powerful surrogates for physical systems, demonstrating increased accuracy, stability, and/or statistical fidelity. Most approaches rely…
cs.LG2024
Tackling the Accuracy-Interpretability Trade-off in a Hierarchy of Machine Learning Models for the Prediction of Extreme Heatwaves
Alessandro Lovo, Amaury Lancelin, Corentin Herbert +1
When performing predictions that use Machine Learning (ML), we are mainly interested in performance and interpretability. This generates a natural trade-off, where complex models g…