Researchers have demonstrated that machine learning algorithms and symbolic regression can accurately predict the ultimate moment capacity and failure modes of long-bolted steel connections in modular ...

A physics-aware, uncertainty-guided deep learning surrogate has been shown to replace expensive circuit simulations when ...

A curated list of awesome AI tools, libraries, papers, datasets, and frameworks that accelerate scientific discovery — from physics and chemistry to biology, materials, and beyond. - ...

This Review discusses the main results obtained in training end-to-end neural architectures for guidance and control of interplanetary transfers, planetary landings, and close-proximity operations, ...

The conflict between stiffness and toughness is a fundamental problem in engineering materials design. However, the systematic discovery of microstructured composites with optimal stiffness-toughness ...

An implementation of Giuseppe Paleologo's Rademacher Antiserum, designed to assess strategy performance consistency through Rademacher complexity and RAS-adjusted Sharpe Ratios. This code evaluates ...