Machine Learning the Tangent Space of Dynamical Instabilities from Data. - Antoine Blanchard; Themistoklis P. Sapsis (CoRR, 2019)

Analytical Description of Optimally Time-Dependent Modes for Reduced-Order Modeling of Transient Instabilities. - Antoine Blanchard; Themistoklis P. Sapsis (SIAM J. Appl. Dyn. Syst., 2019)

Bayesian Optimization with Output-Weighted Importance Sampling. - Antoine Blanchard; Themistoklis P. Sapsis (CoRR, 2020)

Informative Path Planning for Anomaly Detection in Environment Exploration and Monitoring. - Antoine Blanchard; Themistoklis P. Sapsis (CoRR, 2020)

Output-Weighted Importance Sampling for Bayesian Experimental Design and Uncertainty Quantification. - Antoine Blanchard; Themistoklis P. Sapsis (CoRR, 2020)

Output-Weighted Sampling for Multi-Armed Bandits with Extreme Payoffs. - Yibo Yang; Antoine Blanchard; Themistoklis P. Sapsis; Paris Perdikaris (CoRR, 2021)

Bayesian optimization with output-weighted optimal sampling. - Antoine Blanchard; Themistoklis P. Sapsis (J. Comput. Phys., 2021)

Output-Weighted Optimal Sampling for Bayesian Experimental Design and Uncertainty Quantification. - Antoine Blanchard; Themistoklis P. Sapsis (SIAM/ASA J. Uncertain. Quantification, 2021)

A Multi-Scale Deep Learning Framework for Projecting Weather Extremes. - Antoine Blanchard; Nishant Parashar; Boyko A. Dodov; Christian Lessig; Themistoklis P. Sapsis (CoRR, 2022)

TAUDiff: Improving statistical downscaling for extreme weather events using generative diffusion models. - Rahul Sundar; Nishant Parashar; Antoine Blanchard; Boyko A. Dodov (CoRR, 2024)

Continuous latent representations for modeling precipitation with deep learning. - Gokul Radhakrishnan; Rahul Sundar; Nishant Parashar; Antoine Blanchard; Daiwei Wang; Boyko A. Dodov (CoRR, 2024)