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advanced_ml

ai-collection

The Generative AI Landscape - A Collection of Awesome Generative AI Applications

awesome-best-papers

Collect awesome best papers from top AI conferences.

awesome-deep-graph-clustering

Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).

awesome-deep-learning-papers

The most cited deep learning papers

awesome-graph-classification

A collection of important graph embedding, classification and representation learning papers with implementations.

awesome-llm4graph-papers

[KDD'2024 Survey+Tutorial] "LLM4Graph: A Survey of Large Language Models for Graphs"

awesome-network-analysis

A curated list of awesome network analysis resources.

awesome-network-embedding

A curated list of network embedding techniques.

bidirectional-random-walk

Random Walk (Personalized PageRank) Algorithms for Large Graphs

cfane

Code for paper Unsupervised Attributed Network Embedding via Cross Fusion (WSDM 2021)

cls-metrics

Clustering evaluation metrics: RI, NMI and Conductance

clustering

Implemented different clustering algorithms and evaluated its efficiency

computing-communities-in-large-networks-using-random-walks

Implementation of a random-walk based algorithm Walktrap to efficiently find clusters in graphs.

dag-gnn

deepgnn

DeepGNN is a framework for training machine learning models on large scale graph data.

deeplearning

Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

deeplearningbook-chinese

Deep Learning Book Chinese Translation

delft

a Deep Learning Framework for Text

dictsentibert

Last Dance for Peking University

dynamic_network_embedding

dynamicppe

Code for the KDD21 paper "Subset Node Representation Learning over Large Dynamic Graphs"

er

evalne

Source code for EvalNE, a Python library for evaluating Network Embedding methods.

experimenttools

XTlib is an API and command line tool for scaling and managing ML experiments. The goal of XTLib is to enable you to effortlessly organize and scale your ML experiments. Our tools offer an incremental approach to adoption, so you can begin realizing benefits immediately..

faster-graph-embeddings

Faster graph embeddings via coarsening (ICML 2020)

fasth

Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.

fbpca

Fast Randomized PCA/SVD

funk-svd

:zap: A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize

gem