Python Graph-networks Resources

ICS-Visualizer is an interactive Industrial Control Systems (ICS) network graph that contains up-to-date ICS metadata (Name, company, port, user manua

Pointer networks Tensorflow2 原文：https://arxiv.org/abs/1506.03134 仅供参考与学习，内含代码备注 环境 tensorflow==2.6.0 tqdm matplotlib numpy 《pointer networks》阅读笔记 应用场景

Overview Metrinome is an all-purpose tool for working with code complexity metrics. It can be used as both a REPL and API, and includes: Converters to

Py2neo Py2neo is a client library and toolkit for working with Neo4j from within Python applications. The library supports both Bolt and HTTP and prov

Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks This is our Pytorch implementation for the paper: Zirui Zhu, Chen Gao, Xu C

Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods Introduction Graph Neural Networks (GNNs) have demonstrated

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

Homepage | Paper | Datasets | Leaderboard | Documentation Graph Robustness Benchmark (GRB) provides scalable, unified, modular, and reproducible evalu

Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp

GDN A tensorflow=1.13 implementation of Deconvolutional Networks on Graph Data (NeurIPS 2021) Abstract In this paper, we consider an inverse problem i

SGMNet Implementation PyTorch implementation of SGMNet for ICCV'21 paper "Learning to Match Features with Seeded Graph Matching Network", by Hongkai C

InterpretableMDE A PyTorch implementation for "Towards Interpretable Deep Networks for Monocular Depth Estimation" paper. arXiv link: https://arxiv.or

Conditional Variational Capsule Network for Open Set Recognition This repository hosts the official code related to "Conditional Variational Capsule N

Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods This is the code repository to accompany the EMNLP 2021 paper on ad

Dynamic Data Augmentation with Gating Networks This is an official PyTorch implementation of the paper Dynamic Data Augmentation with Gating Networks

DEDMAP is a Simple but Powerful, Clever and Flexible Cross-Platform Port Scanning tool made with ease to use and convenience in mind. Both TCP

Package Description The difficulties in acquiring spectroscopic data have been a major challenge for supernova surveys. snlstm is developed to provide

snn-localization repo PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch. Install Dependencies Orig

CaGCN This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration". Paper L

UAV-Networks Simulator - Autonomous Networking - A.A. 20/21 UAV-Networks-Routing is a Python simulator for experimenting routing algorithms and mac pr

Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp

ADGCL : Adversarial Graph Augmentation to Improve Graph Contrastive Learning Introduction This repo contains the Pytorch [1] implementation of Adversa

Code for sound field predictions in domains with impedance boundaries. Used for generating results from the paper

Efficient Sharpness-aware Minimization for Improved Training of Neural Networks Code for “Efficient Sharpness-aware Minimization for Improved Training

Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro

Project Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs, https://arxiv.org/pdf/2111.01940.pdf. Authors Truong Son Hy

Recursive Bayesian Networks This repository contains the code to reproduce the results from the NeurIPS 2021 paper Lieck R, Rohrmeier M (2021) Recursi

Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback This is our Pytorch implementation for the paper: Yinwei Wei,

RHGN Source code for CIKM 2021 paper for Relation-aware Heterogeneous Graph for User Profiling Dependencies torch==1.6.0 torchvision==0.7.0 dgl==0.7.1

RM Operation can equivalently convert ResNet to VGG, which is better for pruning; and can help RepVGG perform better when the depth is large.

Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods Introduction Graph Neural Networks (GNNs) have demonstrated

DistMIS Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image Segmentation. DistriMIS Distributing Deep Learning Hyperparameter Tuning

Edge Independent Graph Models Code for the paper: "On the Power of Edge Independent Graph Models" Sudhanshu Chanpuriya, Cameron Musco, Konstantinos So

FastCover: A Self-Supervised Learning Framework for Multi-Hop Influence Maximization in Social Networks by Anonymous.

Can we learn gradients by Hamiltonian Neural Networks? This project was carried out as part of the Optimization for Machine Learning course (CS-439) a

IGCN : Image-to-graph convolutional network IGCN is a learning framework for 2D/3D deformable model registration and alignment, and shape reconstructi

Sample-specific Bayesian Networks A framework for estimating the structures and parameters of Bayesian networks (DAGs) at per-sample or per-patient re

Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems This repository is the official implementation of Rever

RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining Our code is based on Learning Attention-based Embed

Data and Code for paper Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge Graph is available f

MedAI: Transparency in Medical Image Segmentation What is this repo This repo contains the code and experiments that are implemented to contribute in

DSP: Trajectory Prediction with Graph-based Dual-scale Context Fusion Introduction This is the project page of the paper Lu Zhang, Peiliang Li, Jing C

Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (Local-Lip) Introduction TL;DR: We propose an efficient and trainabl

Generative Adversarial Networks(GANs) Vanilla GAN ClusterGAN Vanilla GAN Model Structure Final Generator Structure A MLP with 2 hidden layers of hidde

Diverse Motion Stylization (Official) This is the official Pytorch implementation of this paper. Diverse Motion Stylization for Multiple Style Domains

DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021] Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng

A large-scale database for graph representation learning

UltraGCN This is our Pytorch implementation for our CIKM 2021 paper: Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He. UltraGCN: A

Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks This repository contains the code and pre-trained

Wide-Networks This repository contains the code of various experiments on wide neural networks. In particular, we implement classes for abc-parameteri

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Abstract Graph Neural Networks (GNNs) are widely used on a

OnsagerNet Learning hidden low dimensional dyanmics using a Generalized Onsager Principle and neural networks This is the original pyTorch implemenati

Face-Detection-with-MTCNN Face detection is a computer vision problem that involves finding faces in photos. It is a trivial problem for humans to sol

Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN) This is the implementation of the paper Multi-Age

Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach This is the implementation of traffic prediction code in DTMP based on PyTo

stock-graph-python Simple GUI python app to show a stocks graph performance. Made with Matplotlib and Tiingo. Tiingo API Key You will need to add your

The Network Simulator, Version 3 Table of Contents: An overview Building ns-3 Running ns-3 Getting access to the ns-3 documentation Working with the d

ParNet Custom Implementation of Non-deep Networks arXiv:2110.07641 Ankit Goyal, Alexey Bochkovskiy, Jia Deng, Vladlen Koltun Official Repository https

Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric

Ansible Playbook Grapher ansible-playbook-grapher is a command line tool to create a graph representing your Ansible playbook plays, tasks and roles.

Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering

Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks Yonggan Fu, Qixuan Yu, Yang Zhang, S

Heterogeneous Temporal Graph Neural Network This repository contains the datasets and source code of HTGNN. run_mag.ipynb is the training and testing

Gradient representations in ReLU networks as similarity functions by Dániel Rácz and Bálint Daróczy. This repo contains the python code related to our

Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro

Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at

BMVC 2021 BI-GConv: Boundary-Aware Input-Dependent Graph Convolution for Biomedical Image Segmentation Necassary Dependencies: PyTorch 1.2.0 Python 3.

VACA Code repository for the paper "VACA: Designing Variational Graph Autoencoders for Interventional and Counterfactual Queries (arXiv)". The impleme

Rot-Pro : Modeling Transitivity by Projection in Knowledge Graph Embedding This repository contains the source code for the Rot-Pro model, presented a

Node Dependent Local Smoothing for Scalable Graph Learning Requirements Environments: Xeon Gold 5120 (CPU), 384GB(RAM), TITAN RTX (GPU), Ubuntu 16.04

L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated photonic circuit states under challenging physical constraints, then performs photonic core mapping via combined analytical solving and zeroth-order optimization.

Temporal-attentive-Covariance-Pooling-Networks-for-Video-Recognition This is an implementation of TCPNet. Introduction For video recognition task, a g

SparseCard Code for approximate graph reduction techniques for cardinality-based DSFM, from paper "Approximate Decomposable Submodular Function Minimi

Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks Setup This implementation is based on PyTorch = 1.0.0. Smal

SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs SMORE is a a versatile framework that scales multi-hop query emb

SimplEx - Explaining Latent Representations with a Corpus of Examples Code Author: Jonathan Crabbé ([email protected]) This repository contains the imp

OneFlow OneFlow is a performance-centered and open-source deep learning framework. Latest News Version 0.5.0 is out! First class support for eager exe

Hierarchical User Intent Graph Network for Multimedia Recommendation This is our Pytorch implementation for the paper: Hierarchical User Intent Graph

Number recognition Recognize numbers from a 28 x 28 image using neural networks Usage This is an example of a simple usage of number-recognition NOTE:

With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the moment, only TensorFlow sequential models are supported. Interfaces to either the Pyomo or Gurobi modeling environments are offered.

Video Matting via Consistency-Regularized Graph Neural Networks Project Page | Real Data | Paper Installation Our code has been tested on Python 3.7,

Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati

Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training Code for our paper "Predicting lncRNA–protein interactio

ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica

Space Time Recurrent Memory Network - Pytorch (wip) Implementation of Space Time Recurrent Memory Network, recurrent network competitive with attentio

mito-network-sharing Sharing of contents on mitochondrial encounter networks Required: R with igraph, brainGraph, ggplot2, and XML libraries; igraph l

Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.

Exponential Graph is Provably Efficient for Decentralized Deep Training This code repository is for the paper Exponential Graph is Provably Efficient

The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C

The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C

Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con

A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.

Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+

A PyTorch Implementation of GGNN This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated G

Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson

Word Counter By EBUS Coding Club Count the frequency of letters or words in a text file and show a graph. Requirements Python 3.9 or higher matplotlib

DPGNN This repository is an official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Im

DyGED Dynamic Graph Event Detection Get Started pip install -r requirements.txt TODO Paper link to arxiv, and how to cite. Twitter Weather dataset tra

HMemNetworks Code and documentation for Harmonic Memory Networks, a series of models for compositionally assembling representations of graph elements

Random-walk Embedding Framework This repository is a reference implementation of the random-walk embedding framework as described in the paper: A Broa