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neurips19-graph-protein-design

Generative Models for Graph-Based Protein Design

nnfem.jl

Neural Network Approach for Data-Driven Constitutive Modeling

nri

Neural relational inference for interacting systems - pytorch

onnx

Open standard for machine learning interoperability

paroptbeam

pdnet

PDNET: A fully open-source framework for deep learning protein real-valued distances

peridigm

Peridigm peridynamics code.

phasefield

PRISMS-PF: An Open-Source Phase-Field Modeling Framework

physics-informed-deeponets

pinn-elastodynamics

physics-informed neural network for elastodynamics problem

pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

pinns-tf2.0

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

polymer_metal_interface

Provides some useful information and the LAMMPS input files to model a polymer-metal interface.

probability_cheatsheet

A comprehensive 10-page probability cheatsheet that covers a semester's worth of introduction to probability.

pyauxetic

Python plugin and library for modeling, analyzing, and post-procesing auxetic structures in Abaqus.

pydens

PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks

pygmsh

Gmsh for Python

pysindy

A package for the sparse identification of nonlinear dynamical systems from data

pytorch-seq2seq

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

pytorchgeometrictutorial

Pytorch Geometric Tutorials

pytorchtutorial

PyTorch Tutorials from my YouTube channel

rad

RAD: Reinforcement Learning with Augmented Data

rdcnn

Reaction diffusion system prediction based on convolutional neural network

recurrentdgnn

Deep Recurrent Graph Neural Network

rigid_transform_3d

rosettafold

This package contains deep learning models and related scripts for RoseTTAFold

scema

HMM implementation featuring Deal.II (FE) and LAMMPS (MD)

schnetpack

SchNetPack - Deep Neural Networks for Atomistic Systems

sciann-applications

A place to share problems solved with SciANN