Awesome-LLM: a curated list of Large Language Model

AWS DeepRacer Free Student Workshop: Run faster by using your custom waypoints. Step by Step to learn reinforcement learning,

Code that was used in the Article "An Advanced Guide to AWS DeepRacer"

Build robotics applications with AWS DeepRacer device software and hardware: https://www.amazon.com/dp/B07JMHRKQG

Arduino documentation (docs.arduino.cc)

This project focuses on best practices of object-oriented programming, AWS AI Services, AWS DeepLens, AWS DeepRacer, and AWS DeepComposer.

DeepRacer workshop content

Sunwoda Electronic Co., Ltd, and Tsinghua Berkeley Shenzhen Institute (TBSI) generate the TBSI Sunwoda Battery Dataset. We open-source this dataset to inspire more data-driven novel material verifi…

Data-parallel PINNs with Horovod

PINEURODEs is a repository collecting CMS group research work on the application of neural (stochastic/ordinary) differential equations and physically-informed neural networks to model complex mult…

Physics-based machine learning with dynamic Boltzmann distributions

Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants. Proceedings of the Royal Society A.

Official imprementation of the paper "A general deep learning method for computing molecular parameters of viscoelastic constitutive model by solving an inverse problem"

Going through the tutorial on Physics-informed Neural Networks: https://github.com/madagra/basic-pinn

This repository is the implementation of the paper "A Variational Autoencoder Framework for Robust, Physics-Informed Cyberattack Recognition in Industrial Cyber-Physical Systems"

Physics-informed refinement learning for equation discovery

Navier-Stokes oil dynamics in a rectangular 3D tank, physics-informed neural network approach

The implementation of the paper "A Machine Learning Pressure Emulator for Hydrogen Embrittlement", accepted to ICML 2023 SynS & ML Workshop

Source code for Zero-Shot Wireless Indoor Navigation through Physics-Informed Reinforcement Learning

study code for physics informed machine learning and deep learning

Uncertainty-penalized Bayesian information criterion (UBIC) for PDE Discovery

Nonnegative Tensor Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning

Code for the NeurIPS 2021 paper "Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features"

This repo contains the code for solving Poisson Equation using Physics Informed Neural Networks

Accompanying code for "Weak form generalized Hamiltonian learning"

Smart Tensors Tutorials

Nonnegative Matrix Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning

Using TensorFlow for physics-informed neural networks for scientific machine learning (SciML)

A C++ library for physics-informed spatial and functional data analysis over complex domains.

Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs