Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization

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Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization

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Improved bounds and inference on optimal regimes

Crypto market betas: the limits of predictability and hedging

Spectral Estimators for High-Dimensional Matrix Inference

Partial discharge localization in power transformer tanks using machine learning methods

Health Prediction for Lithium-Ion Batteries Under Unseen Working Conditions

Intermediate complexity atmospheric modeling in complex terrain: is it right?

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

Airborne sensor fusion: Expected accuracy and behavior of a concurrent adjustment

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

OASIS: An integrated optimisation framework for activity scheduling

Exploiting the Signal-Leak Bias in Diffusion Models

Diffusion Moving-Average Adaptation Over Networks

Quantization for Decentralized Learning Under Subspace Constraints

Timing and spatial selection bias in rapid extreme event attribution

Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks

State-Based Versus Time-Based Estimation of the Gait Phase for Hip Exoskeletons in Steady and Transient Walking

Modeling local thermal responses of individuals: Validation of advanced human thermo-physiology models

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