Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
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Updated
Mar 5, 2024 - Python
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Minimal and clean examples of machine learning algorithms implemented in Julia
A NetworkX implementation of Label Propagation from a "Near Linear Time Algorithm to Detect Community Structures in Large-Scale Networks" (Physical Review E 2008).
Pytorch Code for ICLR19 paper: Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning.
A tensorflow implementation of GCN-LPA
Dynamic Graph-Based Label Propagation for Density Peaks Clustering
Semi-supervised learning via Compact Latent Space Clustering
Multi Atlas Segmentation and Morphometric analysis toolkit (MASMAT) for mouse brain MRI
Code and models accompanying "Learning to Associate Words and Images Using a Large-scale Graph"
✨🧬 Refined binning of metagenomic contigs using assembly graphs
Incremental Label Propagation (ILP) - Incremental Semi-Supervised Learning from Streams for Object Classification
Label propagation algorithm for community detection based on node importance and label influence
Mask Propagation and Active Learning in Medical CT Image Segmentation
Code and Datasets for paper "Towards early detection of adverse drug reactions: combining pre-clinical drug structures and post-market safety reports"
The implementation of our MICCAI20 paper "SiamParseNet: Joint Body Parsing and Label Propagation in Infant Movement Videos"
Cross-Domain Kernel Induction for Transfer Learning
The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"
A DGL implementation of "Combining Label Propagation and Simple Models Out-performs Graph Neural Networks" (ICLR 2021).
A Node Influence Based Label Propagation Algorithm for Community Detection in Networks
EECE 5645 Project: Performing community detection on Reddit Hyperlink network dataset and leverage the power of Spark and GraphFrames
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