MITIBMxGraph

Pinned Repositories

dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Language:Python0 0 00
Elliptic2
Official guide of using the Elliptic2 dataset introduced by the paper "The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset"
Language:Python15 2 13
METIS-GKlib
Small modifications to METIS build to include GKlib so that its easier to install dependent libraries related to SALIENT++.
Language:C0 2 00
ogb
Benchmark datasets, data loaders, and evaluators for graph machine learning
Language:Python0 1 00
RevTrack
[ICAIF 2024 Oral] Official PyTorch Implementation of "Identifying Money Laundering Subgraphs on the Blockchain"
Language:Python40
SALIENT
The official SALIENT system described in the paper "Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining".
Language:C++38 4 27
SALIENT_artifact
Artifact evaluation of the paper "Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining"
Language:C++24 3 23
SALIENT_plusplus
The official SALIENT++ system described in the paper "Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching".
Language:C++6 3 23
SALIENT_plusplus_artifact
Artifact for the MLSys 2023 paper "Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching"
Language:C++3 3 20
torch-metis
Version of pytorch-metis that has bindings that directly accept pytorch tensors for constructing metis graphs. No data copies are required to convert from pytorch CSR and Metis's graph representation because METIS uses CSR internally.
Language:Python1 2 00

MITIBMxGraph's Repositories

MITIBMxGraph/SALIENT
The official SALIENT system described in the paper "Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining".
Language:C++38 4 27
MITIBMxGraph/SALIENT_artifact
Artifact evaluation of the paper "Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining"
Language:C++24 3 23
MITIBMxGraph/Elliptic2
Official guide of using the Elliptic2 dataset introduced by the paper "The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset"
Language:Python15 2 13
MITIBMxGraph/SALIENT_plusplus
The official SALIENT++ system described in the paper "Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching".
Language:C++6 3 23
MITIBMxGraph/RevTrack
[ICAIF 2024 Oral] Official PyTorch Implementation of "Identifying Money Laundering Subgraphs on the Blockchain"
Language:Python40
MITIBMxGraph/SALIENT_plusplus_artifact
Artifact for the MLSys 2023 paper "Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching"
Language:C++3 3 20
MITIBMxGraph/torch-metis
Version of pytorch-metis that has bindings that directly accept pytorch tensors for constructing metis graphs. No data copies are required to convert from pytorch CSR and Metis's graph representation because METIS uses CSR internally.
Language:Python1 2 00
MITIBMxGraph/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Language:Python0 0 00
MITIBMxGraph/METIS-GKlib
Small modifications to METIS build to include GKlib so that its easier to install dependent libraries related to SALIENT++.
Language:C0 2 00
MITIBMxGraph/ogb
Benchmark datasets, data loaders, and evaluators for graph machine learning
Language:Python0 1 00