There are 0 repository under graphneuralnetwork topic.
A Deep Graph-based Toolbox for Fraud Detection
A collection of GNN-based fake news detection models.
Enterprise graph machine learning framework for billion-scale graphs for ML scientists and data scientists.
Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
EquiDock: geometric deep learning for fast rigid 3D protein-protein docking
A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X
FUNDED is a novel learning framework for building vulnerability detection models.
WWW2020-One2Multi Graph Autoencoder for Multi-view Graph Clustering
Learning Fraud Detection from research papers and industry applications.
Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
Graph Convolutional Networks for 4-class EEG Classification
Code for reproducing results in GraphMix paper
Artifact for OSDI'21 GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs.
This repository contains a dataset for testing graph classification algorithms, such as Graph Kernels and Graph Neural Networks.
A portable framework to map DFG (dataflow graph, representing an application) on spatial accelerators.
Tracking and Trajectory Prediction
3D Multi-Object Tracking Using Graph Neural Networks with Cross-Edge Modality Attention. http://batch3dmot.cs.uni-freiburg.de
Artifact for OSDI'23: MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms.
Graph Neural Network architecture to solve the decision version of the graph coloring problem (GCP)
A comprehensive collection of GNN works in NeurIPS 2019.
Supporting code for doi 10.1021/acs.jcim.0c01344
Code for Graph Representation of 3D CAD models for Machining Feature Recognition with Deep Learning paper on deep learning from planar B-Rep CAD models.
Research repository for the proposed equivariant graph attention network that operates on large biomolecules proposed by Le et al. (2022)
Codes, data, and baselines for CIKM 2023 Long Paper "Dual Intents Graph Modeling for User-centric Group Discovery"
DiffWire: Inductive Graph Rewiring via the Lovász Bound. In Proceedings of the First Learning on Graphs Conference. 2022. Adrian Arnaiz-Rodriguez, Ahmed Begga, Francisco Escolano and Nuria Oliver.
A Tensorflow implementation of the paper https://arxiv.org/pdf/1803.07710.pdf
A notebook containing implementations of different graph deep node embeddings along with benchmark graph neural network models in tensorflow. This has been taken from https://www.kaggle.com/abhilash1910/nlp-workshop-ml-india-deep-graph-learning to apply GNNs/node embeddings on NLP task.
Official code repository for the papers "Anti-Symmetric DGN: a stable architecture for Deep Graph Networks" accepted at ICLR 2023; "Non-Dissipative Propagation by Anti-Symmetric Deep Graph Networks"; and "Non-Dissipative Propagation by Randomized Anti-Symmetric Deep Graph Networks"
[AAAI 2023] Official implementation of FTM: A Frame-level Timeline Modeling Method for Temporal Graph Representation Learning