A Lightweight and User-Friendly EoH Framework for LLM-driven Automated Algorithm/Heuristic Design Heuristics are indispensable for tackling complex search and optimization problems. However, manual ...

Abstract: Partial differential equations (PDEs) are ubiquitous to the mathematical description of physical phenomena. Typical examples describe the evolution of a field in time as a function of its ...

Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...

Tired of having to handle asynchronous processes for neuroevolution? Do you want to leverage massive vectorization and high-throughput accelerators for Evolution Strategies? evosax provides a ...

We present a Python implementation of a D- and E-region chemistry and ionization code called pyGPI5. Particle precipitation that penetrates into the E- and D-region of the ionosphere-thermosphere ...

Fundamental biological processes, such as tissue morphogenesis during development, rely on the correct sorting of cells. Cellular sorting is governed by basic physical properties such as the adhesion ...