Engineer-To-Order (ETO) Graph Neural Scheduling (GNS) Project
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Updated
May 25, 2024 - Python
Engineer-To-Order (ETO) Graph Neural Scheduling (GNS) Project
A project which aims to abstract the analysis pipeline of a Particle Physics Analysis at ATLAS. This repository is a shared effort of University of Sydney, Duke and DESY.
Enterprise graph machine learning framework for billion-scale graphs for ML scientists and data scientists.
Learning Fraud Detection from research papers and industry applications.
[ECCV 2024]Temporary code for "Ad-HGformer: An Adaptive HyperGraph Transformer for Skeletal Action Recognition"
SREX-GNN improves Genetic Optimization Algorithms by enabling an Graph Neural Network to select the correct "genes" to cross-over
This is the official PyTorch implementation of Structure Embedded Nucleus Classification for Histopathology Images
This repository contains the official implementation of the paper titled Multimodal weighted graph representation for information extraction from visually rich documents.
Official repository for the paper "Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Neural Networks"
Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
Official implementation of the paper "FedLSF: Federated Local Graph Learning via Specformers"
Artifact for OSDI'23: MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms.
This repository is the implementation of the paper Semi-Supervised Classification With Graph Convolutional Networks (aka GCN) by Kipf et al., ICLR 2017.
Explainable Neural Subgraph Matching with Graph Learnable Multi-hop Attention Networks
Reinforcement learning on dynamic knowledge graphs
Implementation of a new hybrid machine learning technique for multi-fidelity surrogates of finite elements models with applications in multi-physics modeling of soft tissues.
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"
LightMHC: A Light Model for pMHC Structure Prediction with Graph Neural Networks
Pytorch Geometric implementation of the "Gravity-Inspired Graph Autoencoders for Directed Link Prediction" paper.
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