sudi2006435

Book-Mathmatical-Foundation-of-Reinforcement-Learning

This is the homepage of a new book entitled "Mathmatical Foundations of Reinforcement Learning."

Conservative_PINNs

We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation property of cPINN is obtained by enforcing the flux continuity in the strong form along the sub-domain interfaces.

deeponet

Learning nonlinear operators via DeepONet

DeepRL-Tutorials

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

DRL_solver

FEMLecture

a very simple and basic finite element programming code based on python

Learning-Python-Physics-Informed-Machine-Learning-PINNs-DeepONets

Physics Informed Machine Learning Tutorials (Pytorch and Jax)

MPM3D-F90

material point method

Physics-Informed-Deep-Learning-Solid-and-Fluid-Mechanics

Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube problems and plane stress linear elasticity boundary value problems

Physics-informed-DeepONets

PINNs-TF2.0

TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).

Pix2Text

Pix In, Latex & Text Out. Recognize Chinese, English Texts, and Math Formulas from Images.

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

Reinforcement-Learning-Notes

Reinforcement-Learning-Notes, start with MDP.

RL