A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks

Related tags

Deep Learningdeep-neural-networksdeep-learningpytorchneural-networkshomomoleculesgraph-neural-networksgnnequivarianceqm9egnn
Overview

Simple implementation of Equivariant GNN

Open In Colab

  • A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction.
  • Just 50 lines of code;
  • The implementation is based on pure PyTorch & Numpy, it has no external packages (like PyTorch-geometric).
  • Closely matches the Mean Absolute Error reported in the paper.

Owner
Arsenii Senya Ashukha
Research scientist at @SamsungLabs AI Center Moscow @bayesgroup
Arsenii Senya Ashukha
GitHub Repository
Code release for NeX: Real-time View Synthesis with Neural Basis Expansion

NeX: Real-time View Synthesis with Neural Basis Expansion Project Page | Video | Paper | COLAB | Shiny Dataset We present NeX, a new approach to novel

538 Jan 09, 2023
Systemic Evolutionary Chemical Space Exploration for Drug Discovery

SECSE SECSE: Systemic Evolutionary Chemical Space Explorer Chemical space exploration is a major task of the hit-finding process during the pursuit of

64 Dec 16, 2022
Image Segmentation with U-Net Algorithm on Carvana Dataset using AWS Sagemaker

Image Segmentation with U-Net Algorithm on Carvana Dataset using AWS Sagemaker This is a full project of image segmentation using the model built with

Htin Aung Lu 1 Jan 04, 2022
LogAvgExp - Pytorch Implementation of LogAvgExp

LogAvgExp - Pytorch Implementation of LogAvgExp for Pytorch Install $ pip instal

Phil Wang 31 Oct 14, 2022
In this project, we'll be making our own screen recorder in Python using some libraries.

Screen Recorder in Python Project Description: In this project, we'll be making our own screen recorder in Python using some libraries. Requirements:

Hassan Shahzad 4 Jan 24, 2022
Reproduces ResNet-V3 with pytorch

ResNeXt.pytorch Reproduces ResNet-V3 (Aggregated Residual Transformations for Deep Neural Networks) with pytorch. Tried on pytorch 1.6 Trains on Cifar

Pau Rodriguez 481 Dec 23, 2022
Playable Video Generation

Playable Video Generation Playable Video Generation Willi Menapace, Stéphane Lathuilière, Sergey Tulyakov, Aliaksandr Siarohin, Elisa Ricci Paper: ArX

Willi Menapace 136 Dec 31, 2022
Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu,

GEMS Lab: Graph Exploration & Mining at Scale, University of Michigan 70 Dec 18, 2022
Soft actor-critic is a deep reinforcement learning framework for training maximum entropy policies in continuous domains.

This repository is no longer maintained. Please use our new Softlearning package instead. Soft Actor-Critic Soft actor-critic is a deep reinforcement

Tuomas Haarnoja 752 Jan 07, 2023
TSDF++: A Multi-Object Formulation for Dynamic Object Tracking and Reconstruction

TSDF++: A Multi-Object Formulation for Dynamic Object Tracking and Reconstruction TSDF++ is a novel multi-object TSDF formulation that can encode mult

ETHZ ASL 130 Dec 29, 2022
《Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching》(CVPR 2020)

This contains the codes for cross-view geo-localization method described in: Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching, CVPR2020.

41 Oct 27, 2022
A colab notebook for training Stylegan2-ada on colab, transfer learning onto your own dataset.

Stylegan2-Ada-Google-Colab-Starter-Notebook A no thrills colab notebook for training Stylegan2-ada on colab. transfer learning onto your own dataset h

Harnick Khera 66 Dec 16, 2022
LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs.

LocUNet LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs. The method utilizes accura

4 Oct 05, 2022
Video Frame Interpolation without Temporal Priors (a general method for blurry video interpolation)

Video Frame Interpolation without Temporal Priors (NeurIPS2020) [Paper] [video] How to run Prerequisites NVIDIA GPU + CUDA 9.0 + CuDNN 7.6.5 Pytorch 1

YoujianZhang 31 Sep 04, 2022
UV matrix decompostion using movielens dataset

UV-matrix-decompostion-with-kfold UV matrix decompostion using movielens dataset upload the 'ratings.dat' file install the following python libraries

2 Oct 18, 2022
Learning from graph data using Keras

Steps to run = Download the cora dataset from this link : https://linqs.soe.ucsc.edu/data unzip the files in the folder input/cora cd code python eda

Mansar Youness 64 Nov 16, 2022
Semantic segmentation task for ADE20k & cityscapse dataset, based on several models.

semantic-segmentation-tensorflow This is a Tensorflow implementation of semantic segmentation models on MIT ADE20K scene parsing dataset and Cityscape

HsuanKung Yang 83 Oct 13, 2022
Code for testing convergence rates of Lipschitz learning on graphs

📈 LipschitzLearningRates The code in this repository reproduces the experimental results on convergence rates for k-nearest neighbor graph infinity L

2 Dec 20, 2021
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li

DamoCV 25 Dec 16, 2022
Weakly-supervised semantic image segmentation with CNNs using point supervision

Code for our ECCV paper What's the Point: Semantic Segmentation with Point Supervision. Summary This library is a custom build of Caffe for semantic i

27 Sep 14, 2022