867 Repositories
Python gpu-knn-snn-graph Libraries
Elevation Mapping on GPU.
Elevation Mapping cupy Overview This is a ros package of elevation mapping on GPU. Code are written in python and uses cupy for GPU calculation. * pla
Accelerated NLP pipelines for fast inference on CPU and GPU. Built with Transformers, Optimum and ONNX Runtime.
Optimum Transformers Accelerated NLP pipelines for fast inference 🚀 on CPU and GPU. Built with 🤗 Transformers, Optimum and ONNX runtime. Installatio
[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
GPU-accelerated Image Processing library using OpenCL
pyclesperanto pyclesperanto is a python package for clEsperanto - a multi-language framework for GPU-accelerated image processing. clEsperanto uses Op
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
(Personalized) Page-Rank computation using PyTorch
torch-ppr This package allows calculating page-rank and personalized page-rank via power iteration with PyTorch, which also supports calculation on GP
A fast poisson image editing implementation that can utilize multi-core CPU or GPU to handle a high-resolution image input.
Poisson Image Editing - A Parallel Implementation Jiayi Weng (jiayiwen), Zixu Chen (zixuc) Poisson Image Editing is a technique that can fuse two imag
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
Use the state-of-the-art m2m100 to translate large data on CPU/GPU/TPU. Super Easy!
Easy-Translate is a script for translating large text files in your machine using the M2M100 models from Facebook/Meta AI. We also privide a script fo
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
Easy Parallel Library (EPL) is a general and efficient deep learning framework for distributed model training.
English | 简体中文 Easy Parallel Library Overview Easy Parallel Library (EPL) is a general and efficient library for distributed model training. Usability
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
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
GPU Programming with Julia - course at the Swiss National Supercomputing Centre (CSCS), ETH Zurich
Course Description The programming language Julia is being more and more adopted in High Performance Computing (HPC) due to its unique way to combine
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 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
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
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
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
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
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
Product-based-recommendation-system - A product based recommendation system which uses Machine learning algorithm such as KNN and cosine similarity
Product-based-recommendation-system A product based recommendation system which
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
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.
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
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable.
Diffrax Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. Diffrax is a JAX-based library providing numerical differe
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.
A framework for GPU based high-performance medical image processing and visualization
FAST is an open-source cross-platform framework with the main goal of making it easier to do high-performance processing and visualization of medical images on heterogeneous systems utilizing both multi-core CPUs and GPUs. To achieve this, FAST use modern C++, OpenCL and OpenGL.
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 Python function for Slurm, to monitor the GPU information
Gpu-Monitor A Python function for Slurm, where I couldn't use nvidia-smi to monitor the GPU information. whole repo is not finish Installation TODO Mo
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
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
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
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
Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them
Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them.
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc)
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed model for heart failure prediction accuracy of 88 percent.
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries.
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv
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
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
Pytorch Performace Tuning, WandB, AMP, Multi-GPU, TensorRT, Triton
Plant Pathology 2020 FGVC7 Introduction A deep learning model pipeline for training, experimentaiton and deployment for the Kaggle Competition, Plant
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
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
OntoProtein: Protein Pretraining With Ontology Embedding
OntoProtein This is the implement of the paper "OntoProtein: Protein Pretraining With Ontology Embedding". OntoProtein is an effective method that mak
Official repository for the paper "On Evaluation Metrics for Graph Generative Models"
On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic
GND-Nets (Graph Neural Diffusion Networks) in TensorFlow.
GNDC For submission to IEEE TKDE. Overview Here we provide the implementation of GND-Nets (Graph Neural Diffusion Networks) in TensorFlow. The reposit
Author Disambiguation using Knowledge Graph Embeddings with Literals
Author Name Disambiguation with Knowledge Graph Embeddings using Literals This is the repository for the master thesis project on Knowledge Graph Embe
This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language Models"
GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language
TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition
TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition Xue, Wenyuan, et al. "TGRNet: A Table Graph Reconstruction Network for Ta
"Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion"(WWW 2021)
STAR_KGC This repo contains the source code of the paper accepted by WWW'2021. "Structure-Augmented Text Representation Learning for Efficient Knowled
CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation
CSKG: The CommonSense Knowledge Graph CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation: AT
Graph Analysis From Scratch
Graph Analysis From Scratch Goal In this notebook we wanted to implement some functionalities to analyze a weighted graph only by using algorithms imp
Roamtologseq - A script loads a json export of a Roam graph and cleans it up for import into Logseq
Roam to Logseq The script loads a json export of a Roam graph and cleans it up f
PyTorchMemTracer - Depict GPU memory footprint during DNN training of PyTorch
A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most
On Evaluation Metrics for Graph Generative Models
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 $k$-Nearest Neighbors and Shared-Nearest Neighbors
GPU implementation of kNN and SNN GPU implementation of $k$-Nearest Neighbors and Shared-Nearest Neighbors Supported by numba cuda and faiss library E
TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow with breakpoints + real-time visualization of the data flowing through the computational graph
TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow (Google's Deep Learning framework) with breakpoints + real-time visualization of the data flowing through the computational graph.
TResNet: High Performance GPU-Dedicated Architecture
TResNet: High Performance GPU-Dedicated Architecture paperV2 | pretrained models Official PyTorch Implementation Tal Ridnik, Hussam Lawen, Asaf Noy, I
This project has Classification and Clustering done Via kNN and K-Means respectfully
This project has Classification and Clustering done Via kNN and K-Means respectfully. It later tests its efficiency via F1/accuracy/recall/precision for kNN and Davies-Bouldin Index for Clustering. The Data is also visually represented.
ECLARE: Extreme Classification with Label Graph Correlations
ECLARE ECLARE: Extreme Classification with Label Graph Correlations @InProceedings{Mittal21b, author = "Mittal, A. and Sachdeva, N. and Agrawal
GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification
GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,
DP2 graph edit codes.
必要なソフト・パッケージ Python3 Numpy JSON Matplotlib 動作確認環境 MacBook Air M1 Python 3.8.2 (arm64) Numpy 1.22.0 Matplotlib 3.5.1 JSON 2.0.9 使い方 draw_time_histgram(
[内测中]前向式Python环境快捷封装工具,快速将Python打包为EXE并添加CUDA、NoAVX等支持。
QPT - Quick packaging tool 快捷封装工具 GitHub主页 | Gitee主页 QPT是一款可以“模拟”开发环境的多功能封装工具,最短只需一行命令即可将普通的Python脚本打包成EXE可执行程序,并选择性添加CUDA和NoAVX的支持,尽可能兼容更多的用户环境。 感觉还可
Colab notebook for openai/glide-text2im.
GLIDE text2im on Colab This repository provides a Colab notebook to produce images conditioned on text prompts with GLIDE [1]. Usage Run text2im.ipynb
Tutorial: Introduction to Graph Machine Learning, with Jupyter notebooks
GraphMLTutorialNLDL22 Tutorial NLDL22: Introduction to Graph Machine Learning, with Jupyter notebooks This tutorial takes place during the conference
Cross-modal Retrieval using Transformer Encoder Reasoning Networks (TERN). With use of Metric Learning and FAISS for fast similarity search on GPU
Cross-modal Retrieval using Transformer Encoder Reasoning Networks This project reimplements the idea from "Transformer Reasoning Network for Image-Te
Code repository for our paper "Learning to Generate Scene Graph from Natural Language Supervision" in ICCV 2021
Scene Graph Generation from Natural Language Supervision This repository includes the Pytorch code for our paper "Learning to Generate Scene Graph fro
Reimplementation of Learning Mesh-based Simulation With Graph Networks
Pytorch Implementation of Learning Mesh-based Simulation With Graph Networks This is the unofficial implementation of the approach described in the pa
Node-level Graph Regression with Deep Gaussian Process Models
Node-level Graph Regression with Deep Gaussian Process Models Prerequests our implementation is mainly based on tensorflow 1.x and gpflow 1.x: python
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing
FairEdit Relevent Publication FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing
Tree-based Search Graph for Approximate Nearest Neighbor Search
TBSG: Tree-based Search Graph for Approximate Nearest Neighbor Search. TBSG is a graph-based algorithm for ANNS based on Cover Tree, which is also an