A Deep Graph-based Toolbox for Fraud Detection
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Updated
Apr 20, 2022 - Python
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
Knowledge-Aware Graph Networks for Commonsense Reasoning (EMNLP-IJCNLP 19)
EquiDock: geometric deep learning for fast rigid 3D protein-protein docking
Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
Learning Fraud Detection from research papers and industry applications.
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
Graph Convolutional Networks for 4-class EEG Classification
Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
Code for reproducing results in GraphMix paper
Artifact for OSDI'21 GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs.
Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch
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.
A portable framework to map DFG (dataflow graph, representing an application) on spatial accelerators.
Artifact for OSDI'23: MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms.
Tracking and Trajectory Prediction
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