Neural-TECMD-Battery-model

Official PyTorch implementation of PTS/PSRN: Fast and efficient symbolic expression discovery through parallelized tree search. Evaluates millions of expressions simultaneously on GPU with automated subtree reuse.

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

PDEBench: An Extensive Benchmark for Scientific Machine Learning

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.

A C daemon that turns your webcam into a light sensor. It will adjust screen backlight based on ambient brightness.

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

Distributed High-Performance Symbolic Regression in Julia