1974 Repositories
Python resilient-swarm-communications-with-meta-graph-convolutional-networks Libraries
PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks
Code for the paper "PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks" (ICPR 2020)
LSTMs (Long Short Term Memory) RNN for prediction of price trends
Price Prediction with Recurrent Neural Networks LSTMs BTC-USD price prediction with deep learning algorithm. Artificial Neural Networks specifically L
Python Implementation of algorithms in Graph Mining, e.g., Recommendation, Collaborative Filtering, Community Detection, Spectral Clustering, Modularity Maximization, co-authorship networks.
Graph Mining Author: Jiayi Chen Time: April 2021 Implemented Algorithms: Network: Scrabing Data, Network Construbtion and Network Measurement (e.g., P
RealTime Emotion Recognizer for Machine Learning Study Jam's demo
Emotion recognizer Table of contents Clone project Dataset Install dependencies Main program Demo 1. Clone project git clone https://github.com/GDSC20
Pytorch implementation of "Get To The Point: Summarization with Pointer-Generator Networks"
About this repository This repo contains an Pytorch implementation for the ACL 2017 paper Get To The Point: Summarization with Pointer-Generator Netwo
This python project contains a class FileProcessor which allows one to grab a file and get some meta data and header information from it
This python project contains a class FileProcessor which allows one to grab a file and get some meta data and header information from it. In the current state, it outputs a PrettyTable to txt file as well as the raw data from that table into a csv.
Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative adversarial networks (GAN)
Flickr-Faces-HQ Dataset (FFHQ) Flickr-Faces-HQ (FFHQ) is a high-quality image dataset of human faces, originally created as a benchmark for generative
Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.
CTC Decoding Algorithms Update 2021: installable Python package Python implementation of some common Connectionist Temporal Classification (CTC) decod
Implements the training, testing and editing tools for "Pluralistic Image Completion"
Pluralistic Image Completion ArXiv | Project Page | Online Demo | Video(demo) This repository implements the training, testing and editing tools for "
Vector AI — A platform for building vector based applications. Encode, query and analyse data using vectors.
Vector AI is a framework designed to make the process of building production grade vector based applications as quickly and easily as possible. Create
image scene graph generation benchmark
Scene Graph Benchmark in PyTorch 1.7 This project is based on maskrcnn-benchmark Highlights Upgrad to pytorch 1.7 Multi-GPU training and inference Bat
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe
This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,
labml.ai Deep Learning Paper Implementations This is a collection of simple PyTorch implementations of neural networks and related algorithms. These i
DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
dm_control: DeepMind Infrastructure for Physics-Based Simulation. DeepMind's software stack for physics-based simulation and Reinforcement Learning en
High-quality implementations of standard and SOTA methods on a variety of tasks.
Uncertainty Baselines The goal of Uncertainty Baselines is to provide a template for researchers to build on. The baselines can be a starting point fo
Code Repository for Liquid Time-Constant Networks (LTCs)
Liquid time-constant Networks (LTCs) [Update] A Pytorch version is added in our sister repository: https://github.com/mlech26l/keras-ncp This is the o
Compare neural networks by their feature similarity
PyTorch Model Compare A tiny package to compare two neural networks in PyTorch. There are many ways to compare two neural networks, but one robust and
Official Code for "Non-deep Networks"
Non-deep Networks arXiv:2110.07641 Ankit Goyal, Alexey Bochkovskiy, Jia Deng, Vladlen Koltun Overview: Depth is the hallmark of DNNs. But more depth m
Codebase for Time-series Generative Adversarial Networks (TimeGAN)
Codebase for Time-series Generative Adversarial Networks (TimeGAN)
Pytorch implementation of the paper Time-series Generative Adversarial Networks
TimeGAN-pytorch Pytorch implementation of the paper Time-series Generative Adversarial Networks presented at NeurIPS'19. Jinsung Yoon, Daniel Jarrett
Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight)
[NeurIPS 2021 Spotlight] HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning [Paper] This is Official PyTorch implementatio
Identify the emotion of multiple speakers in an Audio Segment
MevonAI - Speech Emotion Recognition Identify the emotion of multiple speakers in a Audio Segment Report Bug · Request Feature Try the Demo Here Table
Code accompanying "Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity," accepted to IEEE SSCI ICES 2021
Evolving-spiking-neuron-cellular-automata-and-networks-to-emulate-in-vitro-neuronal-activity Code accompanying "Evolving spiking neuron cellular autom
Official PyTorch Implementation of Learning Architectures for Binary Networks
Learning Architectures for Binary Networks An Pytorch Implementation of the paper Learning Architectures for Binary Networks (BNAS) (ECCV 2020) If you
A hifiasm fork for metagenome assembly using Hifi reads.
hifiasm_meta - de novo metagenome assembler, based on hifiasm, a haplotype-resolved de novo assembler for PacBio Hifi reads.
The official implementation of paper Siamese Transformer Pyramid Networks for Real-Time UAV Tracking, accepted by WACV22
SiamTPN Introduction This is the official implementation of the SiamTPN (WACV2022). The tracker intergrates pyramid feature network and transformer in
Temporal Knowledge Graph Reasoning Triggered by Memories
MTDM Temporal Knowledge Graph Reasoning Triggered by Memories To alleviate the time dependence, we propose a memory-triggered decision-making (MTDM) n
Membership Inference Attack against Graph Neural Networks
MIA GNN Project Starter If you meet the version mismatch error for Lasagne library, please use following command to upgrade Lasagne library. pip insta
Official PyTorch implementation of "Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient".
Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient This repository is the official PyTorch implementation of "Edge Rewiring Go
Forecasting Nonverbal Social Signals during Dyadic Interactions with Generative Adversarial Neural Networks
ForecastingNonverbalSignals This is the implementation for the paper Forecasting Nonverbal Social Signals during Dyadic Interactions with Generative A
[ICCV 2021] Code release for "Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks"
Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks By Yikai Wang, Yi Yang, Fuchun Sun, Anbang Yao. This is the pytorc
A graph-to-sequence model for one-step retrosynthesis and reaction outcome prediction.
Graph2SMILES A graph-to-sequence model for one-step retrosynthesis and reaction outcome prediction. 1. Environmental setup System requirements Ubuntu:
This is the official code of L2G, Unrolling and Recurrent Unrolling in Learning to Learn Graph Topologies.
Learning to Learn Graph Topologies This is the official code of L2G, Unrolling and Recurrent Unrolling in Learning to Learn Graph Topologies. Requirem
A library for optimization on Riemannian manifolds
TensorFlow RiemOpt A library for manifold-constrained optimization in TensorFlow. Installation To install the latest development version from GitHub:
Pytorch implementation for the Temporal and Object Quantification Networks (TOQ-Nets).
TOQ-Nets-PyTorch-Release Pytorch implementation for the Temporal and Object Quantification Networks (TOQ-Nets). Temporal and Object Quantification Net
VLG-Net: Video-Language Graph Matching Networks for Video Grounding
VLG-Net: Video-Language Graph Matching Networks for Video Grounding Introduction Official repository for VLG-Net: Video-Language Graph Matching Networ
Dynamic hair modeling from monocular videos using deep neural networks
Dynamic Hair Modeling The source code of the networks for our paper "Dynamic hair modeling from monocular videos using deep neural networks" (SIGGRAPH
A tiny package to compare two neural networks in PyTorch
Compare neural networks by their feature similarity
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
TumorInsight is a Brain Tumor Detection and Classification model built using RESNET50 architecture.
A Brain Tumor Detection and Classification Model built using RESNET50 architecture. The model is also deployed as a web application using Flask framework.
Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks
Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka
Learning Fair Representations for Recommendation: A Graph-based Perspective, WWW2021
FairGo WWW2021 Learning Fair Representations for Recommendation: A Graph-based Perspective As a key application of artificial intelligence, recommende
A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information" (WSDM 2021)
FairGNN A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information" (
Temporal Meta-path Guided Explainable Recommendation (WSDM2021)
Temporal Meta-path Guided Explainable Recommendation (WSDM2021) TMER Code of paper "Temporal Meta-path Guided Explainable Recommendation". Requirement
Code for ICML2019 Paper "Compositional Invariance Constraints for Graph Embeddings"
Dependencies NOTE: This code has been updated, if you were using this repo earlier and experienced issues that was due to an outaded codebase. Please
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation This repository contains the source code of the SIGIR 2019 paper "Reinforcement
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Accuracy-Diversity Trade-off in Recommender Systems via Graph Convolutions
Accuracy-Diversity Trade-off in Recommender Systems via Graph Convolutions This repository contains the code of the paper "Accuracy-Diversity Trade-of
The official implementation of "DGCN: Diversified Recommendation with Graph Convolutional Networks" (WWW '21)
DGCN This is the official implementation of our WWW'21 paper: Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li, DGCN: Diversified Recommendation wi
The implementation of the submitted paper "Deep Multi-Behaviors Graph Network for Voucher Redemption Rate Prediction" in SIGKDD 2021 Applied Data Science Track.
DMBGN: Deep Multi-Behaviors Graph Networks for Voucher Redemption Rate Prediction The implementation of the accepted paper "Deep Multi-Behaviors Graph
This is our implementation of GHCF: Graph Heterogeneous Collaborative Filtering (AAAI 2021)
GHCF This is our implementation of the paper: Chong Chen, Weizhi Ma, Min Zhang, Zhaowei Wang, Xiuqiang He, Chenyang Wang, Yiqun Liu and Shaoping Ma. 2
Code for my ORSUM, ACM RecSys 2020, HeroGRAPH: A Heterogeneous Graph Framework for Multi-Target Cross-Domain Recommendation
HeroGRAPH Code for my ORSUM @ RecSys 2020, HeroGRAPH: A Heterogeneous Graph Framework for Multi-Target Cross-Domain Recommendation Paper, workshop pro
Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks
Bi-TGCF Tensorflow Implementation of BiTGCF: Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks. in CIKM20
Hierarchical Fashion Graph Network for Personalized Outfit Recommendation, SIGIR 2020
hierarchical_fashion_graph_network This is our Tensorflow implementation for the paper: Xingchen Li, Xiang Wang, Xiangnan He, Long Chen, Jun Xiao, and
Bundle Graph Convolutional Network
Bundle Graph Convolutional Network This is our Pytorch implementation for the paper: Jianxin Chang, Chen Gao, Xiangnan He, Depeng Jin and Yong Li. Bun
Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'.
COTREC Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'. Requirements: Python 3.7, Pytorch 1.6.0 Best Hype
Codes for AAAI'21 paper 'Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation'
DHCN Codes for AAAI 2021 paper 'Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation'. Please note that the default link
[ICDMW 2020] Code and dataset for "DGTN: Dual-channel Graph Transition Network for Session-based Recommendation"
DGTN: Dual-channel Graph Transition Network for Session-based Recommendation This repository contains PyTorch Implementation of ICDMW 2020 (NeuRec @ I
The source code for "Global Context Enhanced Graph Neural Network for Session-based Recommendation".
GCE-GNN Code This is the source code for SIGIR 2020 Paper: Global Context Enhanced Graph Neural Networks for Session-based Recommendation. Requirement
Handling Information Loss of Graph Neural Networks for Session-based Recommendation
LESSR A PyTorch implementation of LESSR (Lossless Edge-order preserving aggregation and Shortcut graph attention for Session-based Recommendation) fro
Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction
MGNN-SPred This is our Tensorflow implementation for the paper: WenWang,Wei Zhang, Shukai Liu, Qi Liu, Bo Zhang, Leyu Lin, and Hongyuan Zha. 2020. Bey
This is our Tensorflow implementation for "Graph-based Embedding Smoothing for Sequential Recommendation" (GES) (TKDE, 2021).
Graph-based Embedding Smoothing (GES) This is our Tensorflow implementation for the paper: Tianyu Zhu, Leilei Sun, and Guoqing Chen. "Graph-based Embe
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer
Introduction This is the repository of our accepted CIKM 2021 paper "Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Trans
RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation
RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation Pytorch based implemention of Relational Temporal
Group-Buying Recommendation for Social E-Commerce
Group-Buying Recommendation for Social E-Commerce This is the official implementation of the paper Group-Buying Recommendation for Social E-Commerce (
Knowledge-aware Coupled Graph Neural Network for Social Recommendation
KCGN AAAI-2021 《Knowledge-aware Coupled Graph Neural Network for Social Recommendation》 Environments python 3.8 pytorch-1.6 DGL 0.5.3 (https://github.
Graph Neural Network based Social Recommendation Model. SIGIR2019.
Basic Information: This code is released for the papers: Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang and Meng Wang. A Neural Influence Dif
Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks
SR-HGNN ICDM-2020 《Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks》 Environments python 3.8 pytorch-1.6 DGL 0.5.
A tensorflow implementation of the RecoGCN model in a CIKM'19 paper, titled with "Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation".
This repo contains a tensorflow implementation of RecoGCN and the experiment dataset Running the RecoGCN model python train.py Example training outp
Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems
DANSER-WWW-19 This repository holds the codes for Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recom
Detecting Beneficial Feature Interactions for Recommender Systems, AAAI 2021
Detecting Beneficial Feature Interactions for Recommender Systems (L0-SIGN) This is our implementation for the paper: Su, Y., Zhang, R., Erfani, S., &
Price-aware Recommendation with Graph Convolutional Networks,
PUP This is the official implementation of our ICDE'20 paper: Yu Zheng, Chen Gao, Xiangnan He, Yong Li, Depeng Jin, Price-aware Recommendation with Gr
Self-supervised Graph Learning for Recommendation
SGL This is our Tensorflow implementation for our SIGIR 2021 paper: Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian,and Xing
An index of recommendation algorithms that are based on Graph Neural Networks.
An index of recommendation algorithms that are based on Graph Neural Networks.
CR-Fill: Generative Image Inpainting with Auxiliary Contextual Reconstruction. ICCV 2021
crfill Usage | Web App | | Paper | Supplementary Material | More results | code for paper ``CR-Fill: Generative Image Inpainting with Auxiliary Contex
Acoustic mosquito detection code with Bayesian Neural Networks
HumBugDB Acoustic mosquito detection with Bayesian Neural Networks. Extract audio or features from our large-scale dataset on Zenodo. This repository
Residual2Vec: Debiasing graph embedding using random graphs
Residual2Vec: Debiasing graph embedding using random graphs This repository contains the code for S. Kojaku, J. Yoon, I. Constantino, and Y.-Y. Ahn, R
Source code for The Power of Many: A Physarum Swarm Steiner Tree Algorithm
Physarum-Swarm-Steiner-Algo Source code for The Power of Many: A Physarum Steiner Tree Algorithm Code implements ideas from the following papers: Sher
This folder contains the implementation of the multi-relational attribute propagation algorithm.
MrAP This folder contains the implementation of the multi-relational attribute propagation algorithm. It requires the package pytorch-scatter. Please
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations)
Graph Neural Networks with Learnable Structural and Positional Representations Source code for the paper "Graph Neural Networks with Learnable Structu
Code for “ACE-HGNN: Adaptive Curvature ExplorationHyperbolic Graph Neural Network”
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network This repository is the implementation of ACE-HGNN in PyTorch. Environment pyt
Data and code for ICCV 2021 paper Distant Supervision for Scene Graph Generation.
Distant Supervision for Scene Graph Generation Data and code for ICCV 2021 paper Distant Supervision for Scene Graph Generation. Introduction The pape
Weakly-supervised Text Classification Based on Keyword Graph
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: A lightweight fully convolutional neural network for speech emotion recognition
Light-SERNet This is the Tensorflow 2.x implementation of our paper "Light-SERNet: A lightweight fully convolutional neural network for speech emotion
TicTacToe using Socket Server
TicTacToe using Socket Server This is a project for the class : 18CSC302J - Computer Networks by Dr. S.Babu Contributors Suvodeep Sinha RA191100301010
State of the Art Neural Networks for Generative Deep Learning
pyradox-generative State of the Art Neural Networks for Generative Deep Learning Table of Contents pyradox-generative Table of Contents Installation U
novel deep learning research works with PaddlePaddle
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
Hacking github graph with a easy python script
Hacking-Github-Graph Hacking github graph with a easy python script Requirements git latest version installed. A text editor (eg: vs code, sublime tex
Code to reproduce the experiments from our NeurIPS 2021 paper " The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective"
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.
Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021. Bobo Xi, Jiaojiao Li, Yunsong Li and Qian Du. Code f
Zora is a python program that searches for GeoLocation info for given CIDR networks , with options to search with API or without API
Zora Zora is a python program that searches for GeoLocation info for given CIDR networks , with options to search with API or without API Installing a
ProMP: Proximal Meta-Policy Search
ProMP: Proximal Meta-Policy Search Implementations corresponding to ProMP (Rothfuss et al., 2018). Overall this repository consists of two branches: m
A D3.js plugin that produces flame graphs from hierarchical data.
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.
Medical image analysis framework merging ANTsPy and deep learning
ANTsPyNet A collection of deep learning architectures and applications ported to the python language and tools for basic medical image processing. Bas
Nature-inspired algorithms are a very popular tool for solving optimization problems.
Nature-inspired algorithms are a very popular tool for solving optimization problems. Numerous variants of nature-inspired algorithms have been develo
BioMASS - A Python Framework for Modeling and Analysis of Signaling Systems
Mathematical modeling is a powerful method for the analysis of complex biological systems. Although there are many researches devoted on produ
Unsupervised Image Generation with Infinite Generative Adversarial Networks
Unsupervised Image Generation with Infinite Generative Adversarial Networks Here is the implementation of MICGANs using DCGAN architecture on MNIST da
Composing methods for ML training efficiency
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.
GUI for a Vocal Remover that uses Deep Neural Networks.
GUI for a Vocal Remover that uses Deep Neural Networks.
The official PyTorch implementation for the paper "sMGC: A Complex-Valued Graph Convolutional Network via Magnetic Laplacian for Directed Graphs".
Magnetic Graph Convolutional Networks About The official PyTorch implementation for the paper sMGC: A Complex-Valued Graph Convolutional Network via M