USC DSCI 553 - Foundations & Applications of Data Mining - Spring 2024 - Prof. Wei-Min Shen
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Updated
Jun 8, 2024 - Python
USC DSCI 553 - Foundations & Applications of Data Mining - Spring 2024 - Prof. Wei-Min Shen
Pruning tool to identify small subsets of network partitions that are significant from the perspective of stochastic block model inference. This method works for single-layer and multi-layer networks, as well as for restricting focus to a fixed number of communities when desired.
The SINr approach to train interpretable word and graph embeddings
Network analysis of the authors in the C-CLAMP corpus
Published in GigaScience. Web app for post-GWAS/QTL analysis that performs a slew of novel bioinformatics analyses to cross-reference GWAS/QTL mapping results with a host of publicly available rice databases
Emulating real networks and clusterings using LFR graphs
[NeurIPS 2023] Official implementation of "A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks"
Community Discovery Library
Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.
A tool for community detection and evaluation in weighted networks with positive and negative edges
Social Network Analysis and STEM Education is designed to prepare researchers to apply network analysis in order to better understand and improve teaching and learning.
Detalle de la experiencia como Senior Tech & Digital Acquisition
Repository of the paper "Community detection in bipartite signed networks is highly dependent on parameter choice"
A take-home assignment project for SilverAI application. The topic is similar photo clustering.
Exploratory Principal Component Analysis
PyGenStability: Multiscale community detection with generalized Markov Stability
Pytorch implementation of Polarized message-passing graph neural networks published in Artificial Intelligence, 2024.
Python pipeline to build empirical kinase networks and identify kinase signalling communities from quantitative phosphoproteomics data.
Python Framework for An Investigation into Unsupervised GNN Learning Environments
Fraud detection data generation with configurable degree distribution& community structure, ready for NebulaGraph.
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