1161 Repositories
Python graph-level-representation Libraries
Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"
The Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more" Arxiv preprint Louay Hazami · Rayhane Mama · Ragavan Thurairatn
High level cheatsheet that was designed to make checks on the OSCP more manageable
High level cheatsheet that was designed to make checks on the OSCP more manageable. This repository however could also be used for your own studying or for evaluating test systems like on HackTheBox or TryHackMe. DM me via Twitter (@FindingUrPasswd) to request any specific additions to the content that you think would also be helpful!
Rich Prosody Diversity Modelling with Phone-level Mixture Density Network
Phone Level Mixture Density Network for TTS This repo contains pytorch implementation of paper Rich Prosody Diversity Modelling with Phone-level Mixtu
[CVPR2022] Representation Compensation Networks for Continual Semantic Segmentation
RCIL [CVPR2022] Representation Compensation Networks for Continual Semantic Segmentation Chang-Bin Zhang1, Jia-Wen Xiao1, Xialei Liu1, Ying-Cong Chen2
[ACL 2022] LinkBERT: A Knowledgeable Language Model 😎 Pretrained with Document Links
LinkBERT: A Knowledgeable Language Model Pretrained with Document Links This repo provides the model, code & data of our paper: LinkBERT: Pretraining
Sionna: An Open-Source Library for Next-Generation Physical Layer Research
Sionna: An Open-Source Library for Next-Generation Physical Layer Research Sionna™ is an open-source Python library for link-level simulations of digi
(CVPR 2022 Oral) Official implementation for "Surface Representation for Point Clouds"
RepSurf - Surface Representation for Point Clouds [CVPR 2022 Oral] By Haoxi Ran* , Jun Liu, Chengjie Wang ( * : corresponding contact) The pytorch off
Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds."
DeltaConv [Paper] [Project page] Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds" by Ru
MGFN: Multi-Graph Fusion Networks for Urban Region Embedding was accepted by IJCAI-2022.
Multi-Graph Fusion Networks for Urban Region Embedding (IJCAI-22) This is the implementation of Multi-Graph Fusion Networks for Urban Region Embedding
[CVPR 2022 Oral] Crafting Better Contrastive Views for Siamese Representation Learning
Crafting Better Contrastive Views for Siamese Representation Learning (CVPR 2022 Oral) 2022-03-29: The paper was selected as a CVPR 2022 Oral paper! 2
TigerLily: Finding drug interactions in silico with the Graph.
Drug Interaction Prediction with Tigerlily Documentation | Example Notebook | Youtube Video | Project Report Tigerlily is a TigerGraph based system de
[CVPR 2022] Structured Sparse R-CNN for Direct Scene Graph Generation
Structured Sparse R-CNN for Direct Scene Graph Generation Our paper Structured Sparse R-CNN for Direct Scene Graph Generation has been accepted by CVP
code for TCL: Vision-Language Pre-Training with Triple Contrastive Learning, CVPR 2022
Vision-Language Pre-Training with Triple Contrastive Learning, CVPR 2022 News (03/16/2022) upload retrieval checkpoints finetuned on COCO and Flickr T
Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
6D Rotation Representation for Unconstrained Head Pose Estimation (Pytorch) Paper Thorsten Hempel and Ahmed A. Abdelrahman and Ayoub Al-Hamadi, "6D Ro
Precision Medicine Knowledge Graph (PrimeKG)
PrimeKG Website | bioRxiv Paper | Harvard Dataverse Precision Medicine Knowledge Graph (PrimeKG) presents a holistic view of diseases. PrimeKG integra
[ICML 2022] The official implementation of Graph Stochastic Attention (GSAT).
Graph Stochastic Attention (GSAT) The official implementation of GSAT for our paper: Interpretable and Generalizable Graph Learning via Stochastic Att
torchlm is aims to build a high level pipeline for face landmarks detection, it supports training, evaluating, exporting, inference(Python/C++) and 100+ data augmentations
💎A high level pipeline for face landmarks detection, supports training, evaluating, exporting, inference and 100+ data augmentations, compatible with torchvision and albumentations, can easily install with pip.
Doing the asl sign language classification on static images using graph neural networks.
SignLangGNN When GNNs 💜 MediaPipe. This is a starter project where I tried to implement some traditional image classification problem i.e. the ASL si
Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation [OpenReview] [arXiv] [Code] The official implementation of GeoDiff: A Geome
ACL 2022: CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph Completion
CAKE ACL 2022: CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph Completion Introduction This is the PyTorch implementation
A Python Library for Graph Outlier Detection (Anomaly Detection)
PyGOD is a Python library for graph outlier detection (anomaly detection). This exciting yet challenging field has many key applications, e.g., detect
PyGCL: A PyTorch Library for Graph Contrastive Learning
PyGCL is a PyTorch-based open-source Graph Contrastive Learning (GCL) library, which features modularized GCL components from published papers, standa
Code Implementation of "Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction".
Span-ASTE: Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction ***** New March 31th, 2022: Scikit-Style API for Easy Usage *****
The implementation our EMNLP 2021 paper "Enhanced Language Representation with Label Knowledge for Span Extraction".
LEAR The implementation our EMNLP 2021 paper "Enhanced Language Representation with Label Knowledge for Span Extraction". See below for an overview of
CompleX Group Interactions (XGI) provides an ecosystem for the analysis and representation of complex systems with group interactions.
XGI CompleX Group Interactions (XGI) is a Python package for the representation, manipulation, and study of the structure, dynamics, and functions of
Code for our paper "Graph Pre-training for AMR Parsing and Generation" in ACL2022
AMRBART An implementation for ACL2022 paper "Graph Pre-training for AMR Parsing and Generation". You may find our paper here (Arxiv). Requirements pyt
LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT
LightHuBERT LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT | Github | Huggingface | SUPER
[ICLR 2022] Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators
AMOS This repository contains the scripts for fine-tuning AMOS pretrained models on GLUE and SQuAD 2.0 benchmarks. Paper: Pretraining Text Encoders wi
[CVPR 2022 Oral] Rethinking Minimal Sufficient Representation in Contrastive Learning
Rethinking Minimal Sufficient Representation in Contrastive Learning PyTorch implementation of Rethinking Minimal Sufficient Representation in Contras
Code for the SIGIR 2022 paper "Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion"
MKGFormer Code for the SIGIR 2022 paper "Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion" Model Architecture Illu
Code for the Findings of NAACL 2022(Long Paper): AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks
AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks arXiv link: upcoming To be published in Findings of NA
Source code for "A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction" @ NAACL 2022
TSAR Source code for NAACL 2022 paper: A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction. 🔥 Introduction We focus on extra
DeepGNN is a framework for training machine learning models on large scale graph data.
DeepGNN Overview DeepGNN is a framework for training machine learning models on large scale graph data. DeepGNN contains all the necessary features in
[SIGIR22] Official PyTorch implementation for "CORE: Simple and Effective Session-based Recommendation within Consistent Representation Space".
CORE This is the official PyTorch implementation for the paper: Yupeng Hou, Binbin Hu, Zhiqiang Zhang, Wayne Xin Zhao. CORE: Simple and Effective Sess
[arXiv22] Disentangled Representation Learning for Text-Video Retrieval
Disentangled Representation Learning for Text-Video Retrieval This is a PyTorch implementation of the paper Disentangled Representation Learning for T
Official public repository of paper "Intention Adaptive Graph Neural Network for Category-Aware Session-Based Recommendation"
Intention Adaptive Graph Neural Network (IAGNN) This is the official repository of paper Intention Adaptive Graph Neural Network for Category-Aware Se
Call-graph profiling for TwinCAT 3
Twingrind This project brings profiling to TwinCAT PLCs. The general idea of the implementation is as follows. Twingrind is a TwinCAT library that inc
Author: Wenhao Yu ([email protected]). ACL 2022. Commonsense Reasoning on Knowledge Graph for Text Generation
Diversifying Commonsense Reasoning Generation on Knowledge Graph Introduction -- This is the pytorch implementation of our ACL 2022 paper "Diversifyin
[ICRA 2022] CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation
This is the official implementation of our paper: Bowen Wen, Wenzhao Lian, Kostas Bekris, and Stefan Schaal. "CaTGrasp: Learning Category-Level Task-R
Semantic Data Management - Property Graphs 📈
SDM - Lab 1 @ UPC 👨🏻💻 Table of contents Introduction Property Graph Dataset 1. Introduction This repo is all about what we have done in SDM lab 1
On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks
On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks We provide the code (in PyTorch) and datasets for our paper "On Size-Orient
A simple, high level, easy-to-use open source Computer Vision library for Python.
ZoomVision : Slicing Aid Detection A simple, high level, easy-to-use open source Computer Vision library for Python. Installation Installing dependenc
Repo for WWW 2022 paper: Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval
BiDR Repo for WWW 2022 paper: Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval. Requirements torch==
Tensorflow 1.13.X implementation for our NN paper: Wei Xia, Sen Wang, Ming Yang, Quanxue Gao, Jungong Han, Xinbo Gao: Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation. Neural Networks 145: 1-9 (2022)
Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation Simple implementation of our paper MVGC. The d
Automatically generate GitHub activity!
Commit Bot Automatically generate GitHub activity! We've all wanted to be the developer that commits every day, but that requires a lot of work. Let's
Hl classification bc - A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality
A Network-Based High-Level Data Classification Algorithm Using Betweenness Centr
Digan - Official PyTorch implementation of Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks
DIGAN (ICLR 2022) Official PyTorch implementation of "Generating Videos with Dyn
SafePicking: Learning Safe Object Extraction via Object-Level Mapping, ICRA 2022
SafePicking Learning Safe Object Extraction via Object-Level Mapping Kentaro Wad
SGMC: Spectral Graph Matrix Completion
SGMC: Spectral Graph Matrix Completion Code for AAAI21 paper "Scalable and Explainable 1-Bit Matrix Completion via Graph Signal Learning". Data Format
GraphLily: A Graph Linear Algebra Overlay on HBM-Equipped FPGAs
GraphLily: A Graph Linear Algebra Overlay on HBM-Equipped FPGAs GraphLily is the first FPGA overlay for graph processing. GraphLily supports a rich se
PyTorch implementation of the Crafting Better Contrastive Views for Siamese Representation Learning
Crafting Better Contrastive Views for Siamese Representation Learning This is the official PyTorch implementation of the ContrastiveCrop paper: @artic
Kglab - an abstraction layer in Python for building knowledge graphs
Graph Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, RDFlib, pySHACL, RAPIDS, NetworkX, iGraph, PyVis, pslpython, pyarrow, etc.
A example project's description is a high-level overview of why you’re doing a project.
A example project's description is a high-level overview of why you’re doing a project.
Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction".
TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr
PyTorch-Geometric Implementation of MarkovGNN: Graph Neural Networks on Markov Diffusion
MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi
TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular potentials
TorchMD-net TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks
Code for CCA-SSG model proposed in the NeurIPS 2021 paper From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.
CATE: Computation-aware Neural Architecture Encoding with Transformers
CATE: Computation-aware Neural Architecture Encoding with Transformers Code for paper: CATE: Computation-aware Neural Architecture Encoding with Trans
Community and sentiment analysis based on tweets
The project has set itself the goal of analyzing the thoughts and interaction of Italian users through the social posts expressed through the Twitter platform on the day of the entry into force of the new measures. In particular, we want to research the reference hubs present on the network, but also the sentiment and emotions of peoples with respect to the new limitations.
A general purpose low level programming language written in Python.
A general purpose low level programming language written in Python. Basal is an easy mid level programming language compiling to C. It has an easy syntax, similar to Python, Rust etc.
A high level library for building Discord bots.
Qord A high level library for building Discord bots. 🚧 This library is currently in development. Questions that you are having What is this? This is
Building Ellee — A GPT-3 and Computer Vision Powered Talking Robotic Teddy Bear With Human Level Conversation Intelligence
Using an object detection and facial recognition system built on MobileNetSSDV2 and Dlib and running on an NVIDIA Jetson Nano, a GPT-3 model, Google Speech Recognition, Amazon Polly and servo motors, I built Ellee - a robotic teddy bear who can move her head and converse naturally.
Large-scale Knowledge Graph Construction with Prompting
Large-scale Knowledge Graph Construction with Prompting across tasks (predictive and generative), and modalities (language, image, vision + language, etc.)
FIRA: Fine-Grained Graph-Based Code Change Representation for Automated Commit Message Generation
FIRA is a learning-based commit message generation approach, which first represents code changes via fine-grained graphs and then learns to generate commit messages automatically.
Automatization of BoxPlot graph usin Python MatPlotLib and Excel
BoxPlotGraphAutomation Automatization of BoxPlot graph usin Python / Excel. This file is an automation of BoxPlot-Graph using python graph library mat
A Graph Learning library for Humans
A Graph Learning library for Humans These novel algorithms include but are not limited to: A graph construction and graph searching class can be found
HAIS_2GNN: 3D Visual Grounding with Graph and Attention
HAIS_2GNN: 3D Visual Grounding with Graph and Attention This repository is for the HAIS_2GNN research project. Tao Gu, Yue Chen Introduction The motiv
A minimalist tool to display a network graph.
A tool to get a minimalist view of any architecture This tool has only be tested with the models included in this repo. Therefore, I can't guarantee t
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification
Code for ML, domain generation, graph generation of ABC dataset
This is the repository for codes for ML, domain generation, graph generation of Asymmetric Buckling Columns (ABC) dataset in the paper "Learning Mechanically Driven Emergent Behavior with Message Passing Neural Networks".
Graph Coloring - Weighted Vertex Coloring Problem
Graph Coloring - Weighted Vertex Coloring Problem This project proposes several local searches and an MCTS algorithm for the weighted vertex coloring
Towards Representation Learning for Atmospheric Dynamics (AtmoDist)
Towards Representation Learning for Atmospheric Dynamics (AtmoDist) The prediction of future climate scenarios under anthropogenic forcing is critical
Code Impementation for "Mold into a Graph: Efficient Bayesian Optimization over Mixed Spaces"
Code Impementation for "Mold into a Graph: Efficient Bayesian Optimization over Mixed Spaces" This repo contains the implementation of GEBO algorithm.
Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions"
Graph Convolution Simulator (GCS) Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions" Requirements: PyTor
Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models Benchmark and Efficient Evaluation
Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models Benchmark and Efficient Evaluation This reposi
Project in which we modelise an Among Us problem using graph theories.
Python-AmongUsProblem Project in which we modelise an Among Us problem using graph theories. The rules are as following: Total of 100 players 10 playe
Multi-Object Tracking in Satellite Videos with Graph-Based Multi-Task Modeling
TGraM Multi-Object Tracking in Satellite Videos with Graph-Based Multi-Task Modeling, Qibin He, Xian Sun, Zhiyuan Yan, Beibei Li, Kun Fu Abstract Rece
Pytorch implementation of TailCalibX : Feature Generation for Long-tail Classification
TailCalibX : Feature Generation for Long-tail Classification by Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi [arXiv] [
Build upon neural radiance fields to create a scene-specific implicit 3D semantic representation, Semantic-NeRF
Semantic-NeRF: Semantic Neural Radiance Fields Project Page | Video | Paper | Data In-Place Scene Labelling and Understanding with Implicit Scene Repr
An implementation of IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification
IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification The repostiory consists of the code, results and data set links for
Building a Mario-like, classic platformer game in Python using the PyGame Library
Building a Mario-like, classic platformer game in Python using the PyGame Library
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification Introduction. This package includes the pyth
Reso is a low-level circuit design language and simulator, inspired by things like Redstone, Conway's Game of Life, and Wireworld.
Reso Reso is a low-level circuit design language and simulator, inspired by things like Redstone, Conway's Game of Life, and Wireworld. What is Reso?
Expense Tracker is a very good tool to keep track of your expenseditures and the total money you saved.
Expense Tracker is a very good tool to keep track of your expenseditures and the total money you saved.
LabGraph is a a Python-first framework used to build sophisticated research systems with real-time streaming, graph API, and parallelism.
LabGraph is a a Python-first framework used to build sophisticated research systems with real-time streaming, graph API, and parallelism.
RefineGNN - Iterative refinement graph neural network for antibody sequence-structure co-design (RefineGNN)
Iterative refinement graph neural network for antibody sequence-structure co-des
GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online Debates
GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online Debates Vibhor Agarwal, Sagar Joglekar, Anthony P. Young an
The aim is to extract timeseries water level 2D information for any designed boundaries within the EasyGSH model domain
bct_file_generator_for_EasyGSH The aim is to extract timeseries water level 2D information for any designed boundaries within the EasyGSH model domain
This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (ICLR 2022)
Equivariant Subgraph Aggregation Networks (ESAN) This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (IC
Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data.
Hatchet Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data. It is intended for analyzing
DIR-GNN - Discovering Invariant Rationales for Graph Neural Networks
DIR-GNN "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)
Espial is an engine for automated organization and discovery of personal knowledge
Live Demo (currently not running, on it) Espial is an engine for automated organization and discovery in knowledge bases. It can be adapted to run wit
TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments for IV 2022.
TorchGRL TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffi
Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction".
GNN_PPI Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction". Lear
My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs (GNN, GAT, GraphSAGE, GCN)
machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be
Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers
Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap
RRL: Resnet as representation for Reinforcement Learning
Resnet as representation for Reinforcement Learning (RRL) is a simple yet effective approach for training behaviors directly from visual inputs. We demonstrate that features learned by standard image classification models are general towards different task, robust to visual distractors, and when used in conjunction with standard Imitation Learning or Reinforcement Learning pipelines can efficiently acquire behaviors directly from proprioceptive inputs.
PyTorch implementation of "VRT: A Video Restoration Transformer"
VRT: A Video Restoration Transformer Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, Luc Van Gool Computer
GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration
GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration Stefan Abi-Karam*, Yuqi He*, Rishov Sarkar*, Lakshmi Sathidevi, Zihang Qiao, Co