Python Graph-convolutional-neural-networks Resources

SSR (NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductivefew-shot classification" [Paper] [Project webpage]

PCAN for Multiple Object Tracking and Segmentation This is the offical implementation of paper PCAN for MOTS. We also present a trailer that consists

mPose3D, a mmWave-based 3D human pose estimation model.

SAGCN - Official PyTorch Implementation | Paper | Project Page This is the official implementation of the paper "Steganographer detection via a simila

Dynet A concept I came up which ditches the idea of "layers" in a neural network. Install Copy Dynet.py to your project. Run the example Install matpl

This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy.

g2o - General Graph Optimization Linux: Windows: g2o is an open-source C++ framework for optimizing graph-based nonlinear error functions. g2o has bee

If you are using this code in your own project, please cite our paper: @inproceedings{awiszus2020toadgan, title={TOAD-GAN: Coherent Style Level Gene

Softlearning Softlearning is a deep reinforcement learning toolbox for training maximum entropy policies in continuous domains. The implementation is

Keyword spotting for Microcontrollers This repository consists of the tensorflow models and training scripts used in the paper: Hello Edge: Keyword sp

AdderNet: Do We Really Need Multiplications in Deep Learning? This code is a demo of CVPR 2020 paper AdderNet: Do We Really Need Multiplications in De

SpinalNet: Deep Neural Network with Gradual Input This repository contains scripts for training different variations of the SpinalNet and its counterp

ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).

Orbitals in Python A small collection of tools made by me, that you can use to visualize atomic orbitals in both 2D and 3D in different aspects, and o

SURGE: Sequential Recommendation with Graph Neural Networks This is our TensorFlow implementation for the paper: Sequential Recommendation with Graph

Official code of APHYNITY Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting (ICLR 2021, Oral) Yuan Yin*, Vincent Le Guen*

MassFormer This is the original implementation of MassFormer, a graph transformer for small molecule MS/MS prediction. Check out the preprint on arxiv

ChebLieNet: Invariant spectral graph NNs turned equivariant by Riemannian geometry on Lie groups Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard We

Pruning Self-attentions into Convolutional Layers in Single Path This is the official repository for our paper: Pruning Self-attentions into Convoluti

Hidden-Fold Networks (HFN): Random Recurrent Residuals Using Sparse Supermasks by Ángel López García-Arias, Masanori Hashimoto, Masato Motomura, and J

Dynamic-Graphs-Construction Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Ne

Sharpness-aware Quantization for Deep Neural Networks This is the official repository for our paper: Sharpness-aware Quantization for Deep Neural Netw

CodeGenX is a Code Generation system powered by Artificial Intelligence! It is delivered to you in the form of a Visual Studio Code Extension and is Free and Open-source!

Yolo v4, v3 and v2 for Windows and Linux (neural networks for object detection) Paper YOLO v4: https://arxiv.org/abs/2004.10934 Paper Scaled YOLO v4:

2s-AGCN Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19 Note PyTorch version should be 0.3! For PyTor

Accelerated Sparse Neural Training: A Provable and Efficient Method to FindN:M Transposable Masks Recently, researchers proposed pruning deep neural n

Pruning Self-attentions into Convolutional Layers in Single Path This is the official repository for our paper: Pruning Self-attentions into Convoluti

Fine-grained Sentiment Analysis as Dependency Graph Parsing This repository contains the code and datasets described in following paper: Fine-grained

SwisE Switch spaces for knowledge graph embeddings. Requirements: python3 pytorch numpy tqdm Reproduce the results To reproduce the reported results,

Delve is a Python package for analyzing the inference dynamics of your PyTorch model.

moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar

Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF

DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders Mangal Prakash1, Alexander Krull1,2, Florian Jug2 1Authors contribut

FInite volume Neural Network (FINN) This repository contains the PyTorch code for models, training, and testing, and Python code for data generation t

Sharpness-aware Quantization for Deep Neural Networks Recent Update 2021.11.23: We release the source code of SAQ. Setup the environments Clone the re

Neural 3D Mesh Renderer (CVPR 2018) This repo contains a PyTorch implementation of the paper Neural 3D Mesh Renderer by Hiroharu Kato, Yoshitaka Ushik

Introduction The brain is the perfect place to look for inspiration to develop more efficient neural networks. One of the main differences with modern

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

Symbolic Melody Identification This repository is an unofficial PyTorch implementation of the paper:A Convolutional Approach to Melody Line Identifica

ENN Incubator Collection of in-progress libraries for entity neural networks: Neural Network Architectures for Structured State Entity Gym: Abstractio

Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det

A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow

HAWQ: Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform

Chord Recognition Demo application The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows

GLANet The code for Global and Local Alignment Networks for Unpaired Image-to-Image Translation arxiv Framework: visualization results: Getting Starte

The Joy of Neural Painting Learning Neural Painters Fast! using PyTorch and Fast.ai Blogpost with more details: The Joy of Neural Painting The impleme

Learning Versatile Neural Architectures by Propagating Network Codes Mingyu Ding, Yuqi Huo, Haoyu Lu, Linjie Yang, Zhe Wang, Zhiwu Lu, Jingdong Wang,

MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant

Overview of OpenPNM OpenPNM is a comprehensive framework for performing pore network simulations of porous materials. More Information For more detail

lacmus The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork. The project is being develo

NBFNet: Neural Bellman-Ford Networks This is the official codebase of the paper Neural Bellman-Ford Networks: A General Graph Neural Network Framework

English | 简体中文 Introduction DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks Reference Pat

networkgen A python module to create random networks using network models Usage $

Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

Pigment The problem of partitioning up a skincare regime into parts such that each part does not interfere with itself is equivalent to the minimal cl

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

Official Website: autokeras.com AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras

PlotNeuralNet Latex code for drawing neural networks for reports and presentation. Have a look into examples to see how they are made. Additionally, l

Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li

HiddenLayer A lightweight library for neural network graphs and training metrics for PyTorch, Tensorflow, and Keras. HiddenLayer is simple, easy to ex

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Neural Style Transfer Content Style Output Description: This script runs neural style transfer against the provided content image. The content image m

nsff_pl Neural Scene Flow Fields using pytorch-lightning. This repo reimplements the NSFF idea, but modifies several operations based on observation o

Neural Style Transfer & Neural Doodles Implementation of Neural Style Transfer from the paper A Neural Algorithm of Artistic Style in Keras 2.0+ INetw

DFL-Colab — DeepFaceLab fork for Google Colab This project provides you IPython Notebook to use DeepFaceLab with Google Colaboratory. You can create y

Code has been run on Google Colab, thanks Google for providing computational resources Contents Natural Language Processing（自然语言处理） Text Classificati

This repository contains all of the code and software labs for MIT 6.S191: Introduction to Deep Learning! All lecture slides and videos are available

MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning

TensorFlow Tutorials Original repository on GitHub Original author is Magnus Erik Hvass Pedersen Introduction These tutorials are intended for beginne

What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of

AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

sm_content_clustering A Python module for clustering creators of social media content into networks. Currently supports identifying potential networks

Ohm-s-Law-Visualizer It's an application to calculate I from v and r using Ohm's Law. It can also plot a graph between V vs I. Story I'm doing my Unde

Implementing Graph Convolutional Networks and Information Retrieval Mechanisms using pure Python and NumPy

generate-2D-quadrilateral-mesh-with-neural-networks-and-tree-search This repository contains single-threaded TreeMesh code. I'm Hua Tong, a senior stu

PyTorch reference implementation of "End-to-end optimized image compression with competition of prior distributions" by Benoit Brummer and Christophe

GN-Transformer AST This is the official repository for the paper "GN-Transformer: Fusing AST and Source Code information in Graph Networks". Data Prep

corn-ordinal-neuralnet This repository contains the orginal model code and experiment logs for the paper "Deep Neural Networks for Rank Consistent Ord

TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video Timely handgun detection is a cr

Fisher Induced Sparse uncHanging (FISH) Mask This repo contains the code for Fisher Induced Sparse uncHanging (FISH) Mask training, from "Training Neu

English | 简体中文 Latest News 2021.10.25 Paper "Docking-based Virtual Screening with Multi-Task Learning" is accepted by BIBM 2021. 2021.07.29 PaddleHeli

Point-Unet This is an unofficial implementation of the MICCAI 2021 paper Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segment

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks This is a Pytorch-Lightning implementation of the paper "Self-s

GemNet: Universal Directional Graph Neural Networks for Molecules Reference implementation in PyTorch of the geometric message passing neural network

TensorFlow GNN This is an early (alpha) release to get community feedback. It's under active development and we may break API compatibility in the fut

GNeRF This repository contains official code for the ICCV 2021 paper: GNeRF: GAN-based Neural Radiance Field without Posed Camera. This implementation

alpha-GAN Unofficial pytorch implementation of Rosca, Mihaela, et al. "Variational Approaches for Auto-Encoding Generative Adversarial Networks." arXi

Experimental code for paper: Generative Adversarial Networks as Variational Training of Energy Based Models, under review at ICLR 2017 requirements: T

Unrolled Generative Adversarial Networks Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein arxiv:1611.02163 This repo contains an example notebo

Stacked Generative Adversarial Networks This repository contains code for the paper "Stacked Generative Adversarial Networks", CVPR 2017. Part of the

Language Generation with Recurrent Generative Adversarial Networks without Pre-training Code for training and evaluation of the model from "Language G

Generating Images with Recurrent Adversarial Networks Python (Theano) implementation of Generating Images with Recurrent Adversarial Networks code pro

First Order Divergence for training GANs This repository contains code accompanying the paper First Order Generative Advesarial Netoworks The majority

DRAGAN (Deep Regret Analytic Generative Adversarial Networks) Link to our paper - https://arxiv.org/abs/1705.07215 Pytorch implementation (thanks!) -

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford, Luke Metz, Soumith Chintala All images in t

ComboGAN This is our ongoing PyTorch implementation for ComboGAN. Code was written by Asha Anoosheh (built upon CycleGAN) [ComboGAN Paper] If you use

CaloGAN Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks. This repository c

Bayesian Generative Adversarial Networks in Tensorflow This repository contains the Tensorflow implementation of the Bayesian GAN by Yunus Saatchi and

AttnGAN Pytorch implementation for reproducing AttnGAN results in the paper AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative