Topics / #graph-neural-networks

Graph-neural-networks projects on GitHub

Neural networks operating on graph-structured data like molecules and networks.

As of , the most-starred Graph-neural-networks projects on GitHub are annotated_deep_learning_paper_implementations (67.6K stars), pytorch_geometric (24.1K stars) and DeepLearning (17.8K stars). GitHub.Locker tracks 12 Graph-neural-networks repositories with 202.1K stars combined. The fastest-growing on October 17 was Unsupervised-Log-Anomaly-Detection-Microservices, with +52 stars in a day.

12Projects
202.1KStars in total
+82Stars in a day
Browse in the catalog →github.com/topics/graph-neural-networks ↗

Hot right now

Most stars gained in a day · Oct 17

+52

Unsupervised-Log-Anomaly-Detection-Microservices

chuansirrr/Unsupervised-Log-Anomaly-Detection-Microservices · ★ 979

It is a research-grade, unsupervised anomaly detection framework for microservice logs that combines Transformer, LSTM, and statistical features with graph-based modeling and ensemble scoring to flag unusual log behavior without labeled data.

+10

RuVector

ruvnet/RuVector · ★ 4.6K

RuVector is a Rust-native persistent memory substrate for AI agents, combining local vector embeddings, graph relationships, feedback-driven learning, and memory lifecycle controls so agents can remember across sessions.

+7

annotated_deep_learning_paper_implementations

labmlai/annotated_deep_learning_paper_implementations · ★ 67.6K

A collection of 60+ PyTorch implementations of deep learning papers, each annotated with side-by-side explanatory notes so you can read the code and the math/explanation together.

+3

deep-learning-drizzle

kmario23/deep-learning-drizzle · ★ 13K

A curated index that collects links to full video lectures and course materials for Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision and NLP courses taught at top universities worldwide.

The all-time top

12 projects · by stars

  1. #1 · labmlai/annotated_deep_learning_paper_implementations

    annotated_deep_learning_paper_implementations

    A collection of 60+ PyTorch implementations of deep learning papers, each annotated with side-by-side explanatory notes so you can read the code and the math/explanation together.

    67.6K
  2. #2 · pyg-team/pytorch_geometric

    pytorch_geometric

    PyG (PyTorch Geometric) is a Python library built on PyTorch for writing and training Graph Neural Networks (GNNs) on structured data — graphs and other irregular structures — using methods drawn from many published papers.

    24.1K
  3. #3 · Mikoto10032/DeepLearning

    DeepLearning

    A Chinese-language deep learning tutorial — a huge curated collection of links to courses, books, lecture notes, surveys and code, taking you from math basics through CNNs, GANs, RNNs and GNNs to Kaggle practice and interview prep.

    17.8K
  1. 4

    GNNPapers

    16.8Kthunlp/GNNPapers

    A curated reading list of must-read research papers on graph neural networks (GNN), covering surveys, model architectures, and applications across many domains.

  2. 5

    deepmind-research

    15.2Kgoogle-deepmind/deepmind-research · Jupyter Notebook

    It is Google DeepMind's research repository: implementations and illustrative code that accompany its published papers, released alongside open-source environments and datasets the community can build on.

  3. 6

    DeepLearningExamples

    14.9KNVIDIA/DeepLearningExamples · Jupyter Notebook

    A collection of NVIDIA-maintained, state-of-the-art deep learning reference implementations across computer vision, NLP, recommenders, speech, and more, tuned for reproducible accuracy and performance on NVIDIA Tensor Core GPUs.

  4. 7

    dgl

    14.3Kdmlc/dgl · Python

    DGL is an open-source Python package for deep learning on graphs: it makes it easy to build and train graph neural networks on top of deep learning frameworks you may already use.

  5. 8

    deep-learning-drizzle

    13Kkmario23/deep-learning-drizzle · HTML

    A curated index that collects links to full video lectures and course materials for Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision and NLP courses taught at top universities worldwide.

  6. 9

    maths-cs-ai-compendium

    7.7KHenryNdubuaku/maths-cs-ai-compendium · TypeScript

    An open, unconventional online textbook covering maths, computing and AI from the ground up — intuition first, real-world context, for practitioners who want deep understanding rather than exam survival.

  7. 10

    sutskever-30-implementations

    5.2Kpageman/sutskever-30-implementations · Jupyter Notebook

    It is a from-scratch NumPy implementation suite covering all 30 deep learning papers from Ilya Sutskever's famous reading list, the one he told John Carmack would teach '90% of what matters' in the field.

  8. 11

    RuVector

    4.6Kruvnet/RuVector · Rust

    RuVector is a Rust-native persistent memory substrate for AI agents, combining local vector embeddings, graph relationships, feedback-driven learning, and memory lifecycle controls so agents can remember across sessions.

  9. 12

    Unsupervised-Log-Anomaly-Detection-Microservices

    979chuansirrr/Unsupervised-Log-Anomaly-Detection-Microservices · Python

    It is a research-grade, unsupervised anomaly detection framework for microservice logs that combines Transformer, LSTM, and statistical features with graph-based modeling and ensemble scoring to flag unusual log behavior without labeled data.

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