2258 Repositories
Python graph-attention-network Libraries
Sharing of contents on mitochondrial encounter networks
mito-network-sharing Sharing of contents on mitochondrial encounter networks Required: R with igraph, brainGraph, ggplot2, and XML libraries; igraph l
Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance
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
Exponential Graph is Provably Efficient for Decentralized Deep Training This code repository is for the paper Exponential Graph is Provably Efficient
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".
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 source codes for TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation.
TME The source codes for TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation. Our implementation is based on TG
Official implementation of NeurIPS 2021 paper "Contextual Similarity Aggregation with Self-attention for Visual Re-ranking"
CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We
[NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"
Qu-ANTI-zation This repository contains the code for reproducing the results of our paper: Qu-ANTI-zation: Exploiting Quantization Artifacts for Achie
Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021).
AA-RMVSNet Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021) in PyTorch. paper link: arXiv | CVF Change Log Ju
This is an official PyTorch implementation of Task-Adaptive Neural Network Search with Meta-Contrastive Learning (NeurIPS 2021, Spotlight).
NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti
Python3 program to control Elgato Ring Light on your local network without Elgato's Control Center software
Elgato Light Controller I'm really happy with my Elgato Key Light from an illumination perspective. However, their control software has been glitchy f
Light-weight network, depth estimation, knowledge distillation, real-time depth estimation, auxiliary data.
light-weight-depth-estimation Boosting Light-Weight Depth Estimation Via Knowledge Distillation, https://arxiv.org/abs/2105.06143 Junjie Hu, Chenyou F
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".
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 PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con
Simple PyTorch hierarchical models.
A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.
A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)
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
BMN: Boundary-Matching Network
BMN: Boundary-Matching Network A pytorch-version implementation codes of paper: "BMN: Boundary-Matching Network for Temporal Action Proposal Generatio
Simple python script for automated network scans with random name generator(useful for CTF boxes).
π Automated NMAP script Description Simple python script for automated network scans with random name generator(useful for CTF boxes). Requirements 1
Count the frequency of letters or words in a text file and show a graph.
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
A script that trains a model to recognize handwritten digits using the MNIST data set.
handwritten-digits-recognition A script that trains a model to recognize handwritten digits using the MNIST data set. Then it loads external files and
Official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Imbalance Classification"
DPGNN This repository is an official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Im
ConformalLayers: A non-linear sequential neural network with associative layers
ConformalLayers: A non-linear sequential neural network with associative layers ConformalLayers is a conformal embedding of sequential layers of Convo
Dynamic Graph Event Detection
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
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale
EgonNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale Paper: EgoNN: Egocentric Neural Network for Point Cloud
Harmonic Memory Networks for Graph Completion
HMemNetworks Code and documentation for Harmonic Memory Networks, a series of models for compositionally assembling representations of graph elements
A Broader Picture of Random-walk Based Graph Embedding
Random-walk Embedding Framework This repository is a reference implementation of the random-walk embedding framework as described in the paper: A Broa
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k
Hierarchical probabilistic 3D U-Net, with attention mechanisms (βππ΅π΅π¦π―π΅πͺπ°π― π-ππ¦π΅, ππππ¦π΄ππ¦π΅) and a nested decoder structure with deep supervision (βπππ¦π΅++).
Hierarchical probabilistic 3D U-Net, with attention mechanisms (βππ΅π΅π¦π―π΅πͺπ°π― π-ππ¦π΅, ππππ¦π΄ππ¦π΅) and a nested decoder structure with deep supervision (βπππ¦π΅++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.
Off-policy continuous control in PyTorch, with RDPG, RTD3 & RSAC
arXiv technical report soon available. we are updating the readme to be as comprehensive as possible Please ask any questions in Issues, thanks. Intro
A novel pipeline framework for multi-hop complex KGQA task. About the paper title: Improving Multi-hop Embedded Knowledge Graph Question Answering by Introducing Relational Chain Reasoning
Rce-KGQA A novel pipeline framework for multi-hop complex KGQA task. This framework mainly contains two modules, answering_filtering_module and relati
Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition
GCN_LogsigRNN This repository holds the codebase for the paper: Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition
Wanli Li and Tieyun Qian: Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction, IJCNN 2021
MRefG Wanli Li and Tieyun Qian: "Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction", IJCNN 2021 1. Requirements To reproduc
CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary.
CUP-DNN CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary. The model was trained on the expre
MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021)
MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021) Overview We release the code of the MVFNet (Multi-View Fusion Network).
Implementation of ConvMixer-Patches Are All You Need? in TensorFlow and Keras
Patches Are All You Need? - ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in t
Visualize the electric field of a point charge network.
ElectriPy β‘ Visualize the electric field of a point charges network. π Installation Install ElectriPy package: $ pip install electripy You are all d
A PyTorch-based library for fast prototyping and sharing of deep neural network models.
A PyTorch-based library for fast prototyping and sharing of deep neural network models.
pytorch implementation of the ICCV'21 paper "MVTN: Multi-View Transformation Network for 3D Shape Recognition"
MVTN: Multi-View Transformation Network for 3D Shape Recognition (ICCV 2021) By Abdullah Hamdi, Silvio Giancola, Bernard Ghanem Paper | Video | Tutori
Graveyard is an attempt at open-source reimplementation of DraciDoupe.cz
Graveyard: Place for Dead (and Undead) Graveyard is an attempt at open-source reimplementation of DraciDoupe.cz (referred to as DDCZ in this text). De
Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch
Enformer - Pytorch (wip) Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch. The original tensorflow
Convolutional neural network web app trained to track our infantβs sleep schedule using our Google Nest camera.
Machine Learning Sleep Schedule Tracker What is it? Convolutional neural network web app trained to track our infantβs sleep schedule using our Google
Neo4j Movies Example application with Flask backend using the neo4j-python-driver
Neo4j Movies Application: Quick Start This example application demonstrates how easy it is to get started with Neo4j in Python. It is a very simple we
This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021.
MCGC Description This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021. Datasets Results ACM DBLP IMDB Amazon photos Amazon co
Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.
Convolutional Recurrent Neural Network This software implements the Convolutional Recurrent Neural Network (CRNN), a combination of CNN, RNN and CTC l
Convolutional Neural Network for 3D meshes in PyTorch
MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f
Django database backed celery periodic task scheduler with support for task dependency graph
Djag Scheduler (Dj)ango Task D(AG) (Scheduler) Overview Djag scheduler associates scheduling information with celery tasks The task schedule is persis
Attention-guided gan for synthesizing IR images
SI-AGAN Attention-guided gan for synthesizing IR images This repository contains the Tensorflow code for "Pedestrian Gender Recognition by Style Trans
Spatial-Temporal Transformer for Dynamic Scene Graph Generation, ICCV2021
Spatial-Temporal Transformer for Dynamic Scene Graph Generation Pytorch Implementation of our paper Spatial-Temporal Transformer for Dynamic Scene Gra
Official Code Release for Container : Context Aggregation Network
Container: Context Aggregation Network Official Code Release for Container : Context Aggregation Network Comparion between CNN, MLP-Mixer and Transfor
Adaptive, interpretable wavelets across domains (NeurIPS 2021)
Adaptive wavelets Wavelets which adapt given data (and optionally a pre-trained model). This yields models which are faster, more compressible, and mo
Self-supervised learning on Graph Representation Learning (node-level task)
graph_SSL Self-supervised learning on Graph Representation Learning (node-level task) How to run the code To run GRACE, sh run_GRACE.sh To run GCA, sh
Official implementation of NeurIPS 2021 paper "Contextual Similarity Aggregation with Self-attention for Visual Re-ranking"
CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We
A lightweight library to compare different PyTorch implementations of the same network architecture.
TorchBug is a lightweight library designed to compare two PyTorch implementations of the same network architecture. It allows you to count, and compar
Apply our monocular depth boosting to your own network!
MergeNet - Boost Your Own Depth Boost custom or edited monocular depth maps using MergeNet Input Original result After manual editing of base You can
Key information extraction from invoice document with Graph Convolution Network
Key Information Extraction from Scanned Invoices Key information extraction from invoice document with Graph Convolution Network Related blog post fro
A banking system is a group or network of institutions that provide financial services for us
A banking system is a group or network of institutions that provide financial services for us. These institutions are responsible for operating a payment system, providing loans, taking deposits, and helping with investments.
Mini SCADA. Poll modbus devices by TCP/IP network.
Plans Add saving and loading devices and channels with files or db or someone else. Multitasking system for poll all devices Automatic optimization po
External Network Pentest Automation using Shodan API and other tools.
Chopin External Network Pentest Automation using Shodan API and other tools. Workflow Input a file containing CIDR ranges. Converts CIDR ranges to ind
Facilitates implementing deep neural-network backbones, data augmentations
Introduction Nowadays, the training of Deep Learning models is fragmented and unified. When AI engineers face up with one specific task, the common wa
Code to reproduce the results for Compositional Attention: Disentangling Search and Retrieval.
Compositional-Attention This repository contains the official implementation for the paper Compositional Attention: Disentangling Search and Retrieval
A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.
AMAZ3DSim AMAZ3DSim is a lightweight python-based 3D network multi-agent simulator. It uses a cell-based congestion model. It calculates risk, battery
Meta graph convolutional neural network-assisted resilient swarm communications
Resilient UAV Swarm Communications with Graph Convolutional Neural Network This repository contains the source codes of Resilient UAV Swarm Communicat
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
CRNN paperοΌAn End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition 1. create your ow
The ibet-Prime security token management system for ibet network.
ibet-Prime The ibet-Prime security token management system for ibet network. Features ibet-Prime is an API service that enables the issuance and manag
Network Enhancement implementation in pytorch
network_enahncement_pytorch Network Enhancement implementation in pytorch Research paper Network Enhancement: a general method to denoise weighted bio
Code for reproducing our paper: LMSOC: An Approach for Socially Sensitive Pretraining
LMSOC: An Approach for Socially Sensitive Pretraining Code for reproducing the paper LMSOC: An Approach for Socially Sensitive Pretraining to appear a
A PyTorch-centric hybrid classical-quantum machine learning framework
torchquantum A PyTorch-centric hybrid classical-quantum dynamic neural networks framework. News Add a simple example script using quantum gates to do
This repository contains all source code, pre-trained models related to the paper "An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator"
An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator This is a Pytorch implementation for the paper "An Empirical Study o
Free,Cross-platform,Single-file mass network protocol server simulator
FaPro Free,Cross-platform,Single-file mass network protocol server simulator δΈζReadme Description FaPro is a Fake Protocol Server tool, Can easily sta
Code for paper "Role-based network embedding via structural features reconstruction with degree-regularized constraint"
Role-based network embedding via structural features reconstruction with degree-regularized constraint Train python main.py --dataset brazil-flights
Connects microservices through a mesh of websockets
WebMesh WebMesh is a WebSocket based communication library for microservices. It uses a WebSocket server based on wsproto that distributes clients on
The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition
BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition Boyan Zhou, Quan Cui, Xiu-Shen Wei*, Zhao-Min Chen This repo
Hippocampal segmentation using the UNet network for each axis
Hipposeg Hippocampal segmentation using the UNet network for each axis, inspired by https://github.com/MICLab-Unicamp/e2dhipseg Red: False Positive Gr
JittorVis - Visual understanding of deep learning models
JittorVis: Visual understanding of deep learning model JittorVis is an open-source library for understanding the inner workings of Jittor models by vi
meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)
meProp The codes were used for the paper meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (ICML 2017) [pdf]
ML From Scratch
ML from Scratch MACHINE LEARNING TOPICS COVERED - FROM SCRATCH Linear Regression Logistic Regression K Means Clustering K Nearest Neighbours Decision
A plug-and-play library for neural networks written in Python
A plug-and-play library for neural networks written in Python!
Deep Learning to Create StepMania SM FIles
StepCOVNet Running Audio to SM File Generator Currently only produces .txt files. Use SMDataTools to convert .txt to .sm python stepmania_note_generat
Reddit bot that uses sentiment analysis
Reddit Bot Project 2: Neural Network Boogaloo Reddit bot that uses sentiment analysis from NLTK.VADER WIP_WIP_WIP_WIP_WIP_WIP Link to test subreddit:
Simple CLI python app to show a stocks graph performance. Made with Matplotlib and Tiingo.
stock-graph-python Simple CLI python app to show a stocks graph performance. Made with Matplotlib and Tiingo. Tiingo API Key You will need to add your
ip2domain - get ip to domain, Know the domian corresponding to the local network connection IP
What is Sometimes, we need to know what connections our local machine has, and what are their IP, domain name, program and parameters? get ip to domai
AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation
AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation A pytorch-version implementation codes of paper:
Deep learning library for solving differential equations and more
DeepXDE Voting on whether we should have a Slack channel for discussion. DeepXDE is a library for scientific machine learning. Use DeepXDE if you need
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence
Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python.
What is Retentioneering? Retentioneering is a Python framework and library to assist product analysts and marketing analysts as it makes it easier to
π₯π₯High-Performance Face Recognition Library on PaddlePaddle & PyTorchπ₯π₯
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa
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)
Code image classification of MNIST dataset using different architectures: simple linear NN, autoencoder, and highway network
Deep Learning for image classification pip install -r http://webia.lip6.fr/~baskiotisn/requirements-amal.txt Train an autoencoder python3 train_auto
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
A Partition Filter Network for Joint Entity and Relation Extraction EMNLP 2021
EMNLP 2021 - A Partition Filter Network for Joint Entity and Relation Extraction
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Initial code of an A3C network
A3C-network Initial code of an A3C network Open the python file named as "APL452 Project Report2" The following libraries and packages have been insta
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
An Straight Dilated Network with Wavelet for image Deblurring
SDWNet: A Straight Dilated Network with Wavelet Transformation for Image Deblurring(offical) 1. Introduction This repo is not only used for our paper(
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence
Neural Circuit Policies Enabling Auditable Autonomy Online access via SharedIt Neural Circuit Policies (NCPs) are designed sparse recurrent neural net
Worktory is a python library created with the single purpose of simplifying the inventory management of network automation scripts.
Worktory is a python library created with the single purpose of simplifying the inventory management of network automation scripts.
PG2Net: Personalized and Group PreferenceGuided Network for Next Place Prediction
PG2Net PG2Net:Personalized and Group Preference Guided Network for Next Place Prediction Datasets Experiment results on two Foursquare check-in datase
A PyTorch implementation of SIN: Superpixel Interpolation Network
SIN: Superpixel Interpolation Network This is is a PyTorch implementation of the superpixel segmentation network introduced in our PRICAI-2021 paper:
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