Python Graph-representation Resources

The Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more" Arxiv preprint Louay Hazami   ·   Rayhane Mama   ·   Ragavan Thurairatn

RCIL [CVPR2022] Representation Compensation Networks for Continual Semantic Segmentation Chang-Bin Zhang1, Jia-Wen Xiao1, Xialei Liu1, Ying-Cong Chen2

LinkBERT: A Knowledgeable Language Model Pretrained with Document Links This repo provides the model, code & data of our paper: LinkBERT: Pretraining

RepSurf - Surface Representation for Point Clouds [CVPR 2022 Oral] By Haoxi Ran* , Jun Liu, Chengjie Wang ( * : corresponding contact) The pytorch off

DeltaConv [Paper] [Project page] Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds" by Ru

Multi-Graph Fusion Networks for Urban Region Embedding (IJCAI-22) This is the implementation of Multi-Graph Fusion Networks for Urban Region Embedding

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

Drug Interaction Prediction with Tigerlily Documentation | Example Notebook | Youtube Video | Project Report Tigerlily is a TigerGraph based system de

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

Vision-Language Pre-Training with Triple Contrastive Learning, CVPR 2022 News (03/16/2022) upload retrieval checkpoints finetuned on COCO and Flickr T

6D Rotation Representation for Unconstrained Head Pose Estimation (Pytorch) Paper Thorsten Hempel and Ahmed A. Abdelrahman and Ayoub Al-Hamadi, "6D Ro

PrimeKG Website | bioRxiv Paper | Harvard Dataverse Precision Medicine Knowledge Graph (PrimeKG) presents a holistic view of diseases. PrimeKG integra

Graph Stochastic Attention (GSAT) The official implementation of GSAT for our paper: Interpretable and Generalizable Graph Learning via Stochastic Att

SignLangGNN When GNNs 💜 MediaPipe. This is a starter project where I tried to implement some traditional image classification problem i.e. the ASL si

GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation [OpenReview] [arXiv] [Code] The official implementation of GeoDiff: A Geome

CAKE ACL 2022: CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph Completion Introduction This is the PyTorch implementation

PyGOD is a Python library for graph outlier detection (anomaly detection). This exciting yet challenging field has many key applications, e.g., detect

PyGCL is a PyTorch-based open-source Graph Contrastive Learning (GCL) library, which features modularized GCL components from published papers, standa

LEAR The implementation our EMNLP 2021 paper "Enhanced Language Representation with Label Knowledge for Span Extraction". See below for an overview of

XGI CompleX Group Interactions (XGI) is a Python package for the representation, manipulation, and study of the structure, dynamics, and functions of

AMRBART An implementation for ACL2022 paper "Graph Pre-training for AMR Parsing and Generation". You may find our paper here (Arxiv). Requirements pyt

LightHuBERT LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT | Github | Huggingface | SUPER

AMOS This repository contains the scripts for fine-tuning AMOS pretrained models on GLUE and SQuAD 2.0 benchmarks. Paper: Pretraining Text Encoders wi

Rethinking Minimal Sufficient Representation in Contrastive Learning PyTorch implementation of Rethinking Minimal Sufficient Representation in Contras

MKGFormer Code for the SIGIR 2022 paper "Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion" Model Architecture Illu

AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks arXiv link: upcoming To be published in Findings of NA

DeepGNN Overview DeepGNN is a framework for training machine learning models on large scale graph data. DeepGNN contains all the necessary features in

CORE This is the official PyTorch implementation for the paper: Yupeng Hou, Binbin Hu, Zhiqiang Zhang, Wayne Xin Zhao. CORE: Simple and Effective Sess

Disentangled Representation Learning for Text-Video Retrieval This is a PyTorch implementation of the paper Disentangled Representation Learning for T

Intention Adaptive Graph Neural Network (IAGNN) This is the official repository of paper Intention Adaptive Graph Neural Network for Category-Aware Se

Twingrind This project brings profiling to TwinCAT PLCs. The general idea of the implementation is as follows. Twingrind is a TwinCAT library that inc

Diversifying Commonsense Reasoning Generation on Knowledge Graph Introduction -- This is the pytorch implementation of our ACL 2022 paper "Diversifyin

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 We provide the code (in PyTorch) and datasets for our paper "On Size-Orient

BiDR Repo for WWW 2022 paper: Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval. Requirements torch==

Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation Simple implementation of our paper MVGC. The d

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

DIGAN (ICLR 2022) Official PyTorch implementation of "Generating Videos with Dyn

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 is the first FPGA overlay for graph processing. GraphLily supports a rich se

Crafting Better Contrastive Views for Siamese Representation Learning This is the official PyTorch implementation of the ContrastiveCrop paper: @artic

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.

TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr

MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi

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 fast predictions of the 3D structure in which a small molecule binds to a protein

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 Code for paper: CATE: Computation-aware Neural Architecture Encoding with Trans

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.

Large-scale Knowledge Graph Construction with Prompting across tasks (predictive and generative), and modalities (language, image, vision + language, etc.)

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.

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 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 This repository is for the HAIS_2GNN research project. Tao Gu, Yue Chen Introduction The motiv

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

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 This project proposes several local searches and an MCTS algorithm for the weighted vertex coloring

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" This repo contains the implementation of GEBO algorithm.

Graph Convolution Simulator (GCS) Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions" Requirements: PyTor

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

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

TailCalibX : Feature Generation for Long-tail Classification by Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi [arXiv] [

Semantic-NeRF: Semantic Neural Radiance Fields Project Page | Video | Paper | Data In-Place Scene Labelling and Understanding with Implicit Scene Repr

Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification Introduction. This package includes the pyth

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.

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 Vibhor Agarwal, Sagar Joglekar, Anthony P. Young an

Equivariant Subgraph Aggregation Networks (ESAN) This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (IC

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" (ICLR 2022)

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 TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffi

GNN_PPI Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction". Lear

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 Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap

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.

GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration Stefan Abi-Karam*, Yuqi He*, Rishov Sarkar*, Lakshmi Sathidevi, Zihang Qiao, Co

Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime Created by Prarthana Bhattacharyya. Disclaimer: This is n

OntoProtein This is the implement of the paper "OntoProtein: Protein Pretraining With Ontology Embedding". OntoProtein is an effective method that mak

On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic

GNDC For submission to IEEE TKDE. Overview Here we provide the implementation of GND-Nets (Graph Neural Diffusion Networks) in TensorFlow. The reposit

Author Name Disambiguation with Knowledge Graph Embeddings using Literals This is the repository for the master thesis project on Knowledge Graph Embe

Implementation for "Conditional entropy minimization principle for learning domain invariant representation features". The code is reproduced from thi

Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation Prerequisites This repo is built upon a local copy of transfo

GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language

Bootstrapped Representation Learning on Graphs This is the PyTorch implementation of BGRL Bootstrapped Representation Learning on Graphs The main scri

TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition Xue, Wenyuan, et al. "TGRNet: A Table Graph Reconstruction Network for Ta

STAR_KGC This repo contains the source code of the paper accepted by WWW'2021. "Structure-Augmented Text Representation Learning for Efficient Knowled

CSKG: The CommonSense Knowledge Graph CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation: AT

Hello from magnus Magnus provides four capabilities for data teams: Compute execution plan: A DAG representation of work that you want to get done. In

Graph Analysis From Scratch Goal In this notebook we wanted to implement some functionalities to analyze a weighted graph only by using algorithms imp

Roam to Logseq The script loads a json export of a Roam graph and cleans it up f

CRLT: A Unified Contrastive Learning Toolkit for Unsupervised Text Representation Learning This repository contains the code and relevant instructions

bspcq, q for query A bspc analyzer (utility for bspwm) This is a small program that prints a user friendly, visual representation, of your current bsp

Low Level Variable Length Intermediate Representation Low Level Variable Length

On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic

GPU implementation of kNN and SNN GPU implementation of $k$-Nearest Neighbors and Shared-Nearest Neighbors Supported by numba cuda and faiss library E