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dgsml

DGSML is the first method of semi-supervised meta learning that employs two novel loss functions to learn a predictive domain-invariant representation by taking both labeled and unlabeled samples from different input domains

diffusion-models-pytorch

Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)

diffusion-point-cloud

:thought_balloon: Diffusion Probabilistic Models for 3D Point Cloud Generation (CVPR 2021)

diffusion_models

A series of tutorial notebooks on denoising diffusion probabilistic models in PyTorch

dna-origami

Genetic algorithm for optimizing DNA origami sequences

dpgn

Differentiable Physics-informed Graph Networks

dsw

Distributional Sliced-Wasserstein distance code

e3_diffusion_for_molecules

e3nn_tutorial

repository and website for tutorials on 3d Euclidean equivariant neural networks

egnn-graph_unet

egnn-pytorch

Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

en-transformer

Implementation of E(n)-Transformer, which extends the ideas of Welling's E(n)-Equivariant Graph Neural Network to attention

enqa

A 3D-equivariant neural network for protein structure accuracy estimation

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

fbpinns

Reproduces the results of the paper "Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations".

ferrite.jl

Finite element toolbox for Julia

few-shot-gnn

fracm

Fractional order optimizer for machine learning

gamd

Data and code for graph neural network accelerated molecular dynamics

gated-graph-transformers

Transformers are Graph Neural Networks!

gdc

Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)

gdss

Official Code Repository for the paper "Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations" (ICML 2022)

geneticalgorithmpython

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

geodiff

Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).

geometric-vector-perceptron

Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021

gn.pytorch

gnn-for-glass

gnn-project

A Graph Neural Network project on HIV data

gnnpapers

Must-read papers on graph neural networks (GNN)

google-research

Google Research