Python Graph-prediction Resources

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

93_Python_Data_Analytics_Projects This repository contains all the data analytics projects that I've worked on in python. No. Name 01 001_Cervical_Can

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

Fixing Malfunctional Objects With Learned Physical Simulation and Functional Prediction Figure 1. Teaser. Introduction This paper studies the problem

LAV Learning from All Vehicles Dian Chen, Philipp Krähenbühl CVPR 2022 (also arXiV 2203.11934) This repo contains code for paper Learning from all veh

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

Pancakeswap Sniper Bot PancakeSwap sniper bot. Automated sniping bot to snipe crypto coin launches. How it works The sniping bot can be used in three

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

Project summary This repository contains the implementation of my bachelor degree project. The aim of the project is to apply non-linear feature reduc

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

UTMOS: UTokyo-SaruLab MOS Prediction System Official implementation of "UTMOS: UTokyo-SaruLab System for VoiceMOS Challenge 2022" submitted to INTERSP

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

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

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

Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction Requirements The code has been tested running under Python 3.7.4, with the foll

Note: This repo is adpoted from https://github.com/UNIMIBInside/Smart-Mobility-Prediction. Due to technical reasons, I did not fork their code. Introd

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

OpenSea Bulk Uploader And Trader 100000 NFTs (MAC WINDOWS ANDROID LINUX) Automatically and massively upload and sell your non-fungible tokens on OpenS

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

MAU (NeurIPS2021) Zheng Chang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, Yan Ye, Xinguang Xiang, Wen GAo. Official PyTorch Code for "MAU: A Motion-Aware

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

DLWP: Deep Learning Weather Prediction DLWP is a Python project containing data-

Lottery Purchase Prediction Model Objective and Goal Predict the lottery type th

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

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.

05.income-prediction Predict the income for each percentile of the population (Python) - FRENCH Effectuez une prédiction de revenus Prérequis Pour ce

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

Deeply Supervised, Layer-wise Prediction-aware (DSLP) Transformer for Non-autoregressive Neural Machine Translation

Code for CCA-SSG model proposed in the NeurIPS 2021 paper From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.

Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

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.

B4PPI Benchmarking Pipeline for the Prediction of Protein-Protein Interactions How this benchmarking pipeline has been built, and how to use it, is de

HiPAL Code for KDD'22 Applied Data Science Track submission -- HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electro

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

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

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

Hybrid Machine learning Model Clone the Repository Create a new Directory as assests and download the model from the below link Model Link To Start th

This python library predicts the punctuation of English, Italian, French and German texts. We developed it to restore the punctuation of transcribed spoken language.

This machine learning model was developed for House Prices - Advanced Regression Techniques competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.

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.

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.

VOODOO Revealing supercooled liquid beyond lidar attenuation Explore the docs » Report Bug · Request Feature Table of Contents About The Project Built

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

Project1_Next-Quarter-Game-Design-Prediction What games should I design next quarter? 상황 : 게임회사 데이터팀 합류 문제 : '다음 분기에 어떤 게임을 설계해야할까' Data Description N

CovidcasePrediction A machine learning model for Covid case prediction Problem Statement Using regression algorithms we can able to track the active c

GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online Debates Vibhor Agarwal, Sagar Joglekar, Anthony P. Young an

Introduction This git repo contains the implementation of my ML project on Heart Disease Prediction. This is a real-world machine learning model/proje

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

GoldNanoparticles This GitHub repo consists of Code and Some results of project- Diabetes Treatment using Gold nanoparticles. These Consist of ML Mode

TRINIT_Hum_kuchh_nahi_karenge_ML01 Document Link https://github.com/Jatin-Goyal-552/TRINIT_Hum_kuchh_nahi_karenge_ML01/blob/main/hum_kuchh_nahi_kareng

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

To-Be is a machine learning challenge on CodaLab Platform about Mortality Prediction. The challenge aims to adress the problems of medical imbalanced data classification.

Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python 📊

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

Breast-Cancer-Prediction Trying to predict whether the cancer is benign or malignant using REGRESSION MODELS in Python. Team Members NAME ROLL-NUMBER

machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be

Deep Inertial Prediction For more information and context related to this repo, please refer to our website. Getting Started (non Docker) Note: you wi

Most Simple & Powefull Trade Bot (WINDOWS LINUX) What Are Some Pros And Cons Of Owning A Sniper Bot? While having a sniper bot is typically an advanta

I have collected data about a set of patients, all of whom suffered from the same illness. During their course of treatment, each patient responded to one of 5 medications, Drug A, Drug B, Drug c, Drug x and y. Part of our job is to build a model to find out which drug might be appropriate for a future patient with the same illness. The feature sets of this dataset are Age, Sex, Blood Pressure, and Cholesterol of patients, and the target is the drug that each patient responded to.

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

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

CSPML (crystal structure prediction with machine learning-based element substitution) CSPML is a unique methodology for the crystal structure predicti

This model involves Insurance bill prediction, which was subsequently deployed on Heroku PaaS

This project aim was to predict the price of houses in the Boston area during the great financial crisis through regression, as well as classify houses into different quality categories according to their features. For this we used a kaggle data set.

Predictive_Modelling Gems & Holiday Package Prediction This project is based on 2 cases studies : Gems Price Prediction and Holiday Package prediction

Machine_Learning Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning This project is based on 2 case-studies:

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

LERP : Label-dependent and event-guided interpretable disease risk prediction using EHRs This is the code for the LERP. Dataset The dataset used is MI