Concept

Function approximation

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Function approximation

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On the symmetries in the dynamics of wide two-layer neural networks

Expectation consistency for calibration of neural networks

Bayes-optimal Learning of Deep Random Networks of Extensive-width

The statistical complexity of early-stopped mirror descent

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Learning to Generate the Unknowns as a Remedy to the Open-Set Domain Shift

Physics-enhanced machine learning with symmetry-adapted and long-range representations

The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models

Machine-Learning of Atomic-Scale Properties Based on Physical Principles

Reduced Models for Optimal Control, Shape Optimization and Inverse Problems in Haemodynamics