Python Heterogeneous-Deep-Graph-Infomax Resources

An index of recommendation algorithms that are based on Graph Neural Networks.

Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform This repository is the implementation of "Variable-Rate Deep Image C

StarEnhancer StarEnhancer: Learning Real-Time and Style-Aware Image Enhancement (ICCV 2021 Oral) Abstract: Image enhancement is a subjective process w

Designing a Practical Degradation Model for Deep Blind Image Super-Resolution Kai Zhang, Jingyun Liang, Luc Van Gool, Radu Timofte Computer Vision Lab

Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

Project Name: Which Bollywood Celebrity You look like A Deep learning based streamlit web app which can tell with which bollywood celebrity your face

Residual2Vec: Debiasing graph embedding using random graphs This repository contains the code for S. Kojaku, J. Yoon, I. Constantino, and Y.-Y. Ahn, R

Deep Crop Rotation Paper (to come very soon!) We propose a deep learning approach to modelling both inter- and intra-annual patterns for parcel classi

MrAP This folder contains the implementation of the multi-relational attribute propagation algorithm. It requires the package pytorch-scatter. Please

Graph Neural Networks with Learnable Structural and Positional Representations Source code for the paper "Graph Neural Networks with Learnable Structu

ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network This repository is the implementation of ACE-HGNN in PyTorch. Environment pyt

NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem Liang Xin, Wen Song, Zhiguang

ESPnet: end-to-end speech processing toolkit system/pytorch ver. 1.3.1 1.4.0 1.5.1 1.6.0 1.7.1 1.8.1 1.9.0 ubuntu20/python3.9/pip ubuntu20/python3.8/p

Distant Supervision for Scene Graph Generation Data and code for ICCV 2021 paper Distant Supervision for Scene Graph Generation. Introduction The pape

SALT: Stackelberg Adversarial Regularization Code for Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach, EMNLP 2021. R

Weakly-supervised Text Classification Based on Keyword Graph How to run? Download data Our dataset follows previous works. For long texts, we follow C

Light-SERNet This is the Tensorflow 2.x implementation of our paper "Light-SERNet: A lightweight fully convolutional neural network for speech emotion

pyradox-generative State of the Art Neural Networks for Generative Deep Learning Table of Contents pyradox-generative Table of Contents Installation U

CSP_Deep_EEG This source code is implemented using keras library based on "Automatic ocular artifacts removal in EEG using deep learning" {https://www

Self-Attention Context Network for Hyperspectral Image Classification PyTorch implementation of our method for adversarial attacks and defenses in hyp

Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac

Deep API Deep Learning as Cloud APIs. This project provides pre-trained deep learning models as a cloud API service. A web interface is available as w

Research 发布基于飞桨的前沿研究工作，包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa

Multi-Car Racing Gym Environment This repository contains MultiCarRacing-v0 a multiplayer variant of Gym's original CarRacing-v0 environment. This env

Active Learning for Deep Object Detection via Probabilistic Modeling This repository is the official PyTorch implementation of Active Learning for Dee

Deep Hough Voting for Robust Global Registration, ICCV, 2021 Project Page | Paper | Video Deep Hough Voting for Robust Global Registration Junha Lee1,

Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes Official PyTorch implementation and EmoCause evaluatio

Pytorch Implementation of Deep Orthogonal Fusion of Local and Global Features (DOLG) This is the unofficial PyTorch Implementation of "DOLG: Single-St

About This repository the official PyTorch implementation of Learning Intra-Batch Connections for Deep Metric Learning. The config files contain the s

滑动验证码深度学习识别 本项目使用深度学习 YOLOV3 模型来识别滑动验证码缺口，基于 https://github.com/eriklindernoren/PyTorch-YOLOv3 修改。 只需要几百张缺口标注图片即可训练出精度高的识别模型，识别效果样例： 克隆项目 运行命令： git cl

Hacking-Github-Graph Hacking github graph with a easy python script Requirements git latest version installed. A text editor (eg: vs code, sublime tex

SBEVNet: End-to-End Deep Stereo Layout Estimation This repository contains the code for "SBEVNet: End-to-End Deep Stereo Layout Estimation" paper by D

Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles This project is for the paper: Detecting Errors and Estimating

Deep Markov Factor Analysis (DMFA) Codes and experiments for deep Markov factor analysis (DMFA) model accepted for publication at NeurIPS2021: A. Farn

Code To run: python runner.py new --save SAVE_NAME --data PATH_TO_DATA_DIR --dataset DATASET --model model_name [options] --n 1000 - train - t

Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021. Bobo Xi, Jiaojiao Li, Yunsong Li and Qian Du. Code f

DeepDream ⚠️ If you don't have a gpu with cuda, the style transfer execution time will be much longer Prerequisites Python =3.8.10 How to Install sud

d3-flame-graph A D3.js plugin that produces flame graphs from hierarchical data. If you don't know what flame graphs are, check Brendan Gregg's post.

IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-quality pre-trained models from torchvision, MMLabs, and soon Pytorch Image Models. It orchestrates the end-to-end deep learning workflow allowing to train networks with easy-to-use robust high-performance libraries such as Pytorch-Lightning and Fastai

ANTsPyNet A collection of deep learning architectures and applications ported to the python language and tools for basic medical image processing. Bas

SCAAML (Side Channel Attacks Assisted with Machine Learning) is a deep learning framwork dedicated to side-channel attacks. It is written in python and run on top of TensorFlow 2.x.

MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.

MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.

Unofficial Implementation of MLP-Mixer, gMLP, resMLP, Vision Permutator, S2MLPv2, RaftMLP, ConvMLP, ConvMixer in Jittor and PyTorch! Now, Rearrange and Reduce in einops.layers.jittor are support!!

GUI for a Vocal Remover that uses Deep Neural Networks.

Magnetic Graph Convolutional Networks About The official PyTorch implementation for the paper sMGC: A Complex-Valued Graph Convolutional Network via M

SoGCN: Second-Order Graph Convolutional Networks This is the authors' implementation of paper "SoGCN: Second-Order Graph Convolutional Networks" in Py

DeepOrder Implementation of DeepOrder for the paper "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing". Project

Research 发布基于飞桨的前沿研究工作，包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa

DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors By Anargyros Chatzitofis, Dimitris Zarpalas, Stefanos Kollias

GCond A PyTorch implementation of paper "Graph Condensation for Graph Neural Networks" Code will be released soon. Stay tuned :) Abstract We propose a

About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloade

IGNN Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" [paper] [supp] Prepare datasets 1 Download training dataset

Deep Adversarial Decomposition PDF | Supp | 1min-DemoVideo Pytorch implementation of the paper: "Deep Adversarial Decomposition: A Unified Framework f

Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover

Graph Convolutional Networks This is a TensorFlow implementation of Graph Convolutional Networks for the task of (semi-supervised) classification of n

Simplifying Graph Convolutional Networks Updates As pointed out by #23, there was a subtle bug in our preprocessing code for the reddit dataset. After

SPAGAN in PyTorch This is a PyTorch implementation of the paper "SPAGAN: Shortest Path Graph Attention Network" Prerequisites We prefer to create a ne

Intro This repository contains code to generate data and reproduce experiments from our NeurIPS 2019 paper: Boris Knyazev, Graham W. Taylor, Mohamed R

Graph Convolutional Networks for Temporal Action Localization This repo holds the codes and models for the PGCN framework presented on ICCV 2019 Graph

IsoGCN The official implementation of IsoGCN, presented in the ICLR2021 paper Isometric Transformation Invariant and Equivariant Graph Convolutional N

Simple and Deep Graph Convolutional Networks This repository contains a PyTorch implementation of "Simple and Deep Graph Convolutional Networks".(http

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "

When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Con

Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files

GAT Graph Attention Networks (Veličković et al., ICLR 2018): https://arxiv.org/abs/1710.10903 GAT layer t-SNE + Attention coefficients on Cora Overvie

Residual Gated Graph ConvNets April 24, 2018 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbress

DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re

A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training CVPR 2020”

Densely Connected Convolutional Networks (DenseNets) This repository contains the code for DenseNet introduced in the following paper Densely Connecte

Deep Residual Networks with 1K Layers By Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Microsoft Research Asia (MSRA). Table of Contents Introduc

TorchArrow (Warning: Unstable Prototype) This is a prototype library currently under heavy development. It does not currently have stable releases, an

Collection of Docker images for ML/DL and video processing projects. Overview of images Three types of images differ by tag postfix: base: Python with

This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I

RIFE - Real Time Video Interpolation arXiv | YouTube | Colab | Tutorial | Demo Table of Contents Introduction Collection Usage Evaluation Training and

revisiting-sepconv This is a reference implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation [1] using PyTorch. Given two f

Markov Chain Composer Using Markov Chain to represent relationships between words in song lyrics and then generating new lyrics.. ahem interpretive po

At Bittensor, we are creating an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence.

GraPE GraPE (Graph Processing and Embedding) is a fast graph processing and embedding library, designed to scale with big graphs and to run on both of

Variational Graph Auto-encoder in Pytorch This repository implements variational graph auto-encoder by Thomas Kipf. For details of the model, refer to

This is a repository for the paper of "Well-classified Examples are Underestimated in Classification with Deep Neural Networks" The implementation and

DSN-IQA Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment" Requirements Python =3.8.0 Pytorch =1.7.1 Usage wit

DeepSeaTreasure Environment Installation In order to get started with this environment, you can install it using the following command: python3 -m pip

SSSNET SSSNET: Semi-Supervised Signed Network Clustering For details, please read our paper. Environment Setup Overview The project has been tested on

next_best_view_rl Setup Clone the repository: git clone --recurse-submodules ... In 'third_party/zed-ros-wrapper': git checkout devel Install mujoco `

Kaggle OpenVaccine Models Codebase of deep learning models for inferring stability of mRNA molecules, corresponding to the Kaggle Open Vaccine Challen

Fast Fourier Convolution (FFC) for Image Classification This is the official code of Fast Fourier Convolution for image classification on ImageNet. Ma

IIRNet Direct design of biquad filter cascades with deep learning by sampling random polynomials. Usage git clone https://github.com/csteinmetz1/IIRNe

CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC

Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Official Pytorch implementation of NeurIPS'21 paper "Motif-based Graph Se

DSN-IQA Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment" Requirements Python =3.8.0 Pytorch =1.7.1 Usage wit

Corp-Rel is a PoC of Corpartion Relationship Knowledge Graph System. It's built on top of the Open Source Graph Database: Nebula Graph with a dataset

MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th

Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations This repo contains official code for the NeurIPS 2021 paper Imi

Select, Reduce, Connect This repository contains the code used for the experiments of: "Understanding Pooling in Graph Neural Networks" Setup Install

Instance-based Label Smoothing for Neural Networks Pytorch Implementation of the algorithm. This repository includes a new proposed method for instanc

Recurrent Model-Free RL is a Strong Baseline for Many POMDPs Welcome to the POMDP world! This repo provides some simple baselines for POMDPs, specific

CottonWeeds Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems. requirements pytorch torchsumma

DeepFilterNet A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering. libDF contains Rust code used for dat