PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
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Updated
Jun 13, 2024 - Python
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
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A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
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.
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
Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
The Base interface of the SciML ecosystem
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
Linear operators for discretizations of differential equations and scientific machine learning (SciML)
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)
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