Statistics for topic graph-neural-networks
RepositoryStats tracks 584,797 Github repositories, of these 582 are tagged with the graph-neural-networks topic. The most common primary language for repositories using this topic is Python (425). Other languages include: Jupyter Notebook (72), C++ (11)
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[TPAMI 2024] Awesome Resources of GNNs for Time Series Analysis (GNN4TS)
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统
Official implementation for NeurIPS'24 paper "Generative Semi-supervised Graph Anomaly Detection"
[KDD 2024] Papers about deep learning in epidemic modeling.
Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with...
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
links to conference publications in graph-based deep learning
The official implementation of DiffAbXL benchmarked in the paper "Exploring Log-Likelihood Scores for Ranking Antibody Sequence Designs", formerly titled "Benchmarking Generative Models for Antibody D...
Official implementation for NeurIPS'24 paper "Generative Semi-supervised Graph Anomaly Detection"
[KDD 2024] Papers about deep learning in epidemic modeling.
SupplyGraph | A Benchmark Dataset for Supply Chain Planning using Graph Neural Networks
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Anomaly detection related books, papers, videos, and toolboxes
[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"
The official implementation of DiffAbXL benchmarked in the paper "Exploring Log-Likelihood Scores for Ranking Antibody Sequence Designs", formerly titled "Benchmarking Generative Models for Antibody D...
[NeurIPS 2024] Official implementation for paper "Can Graph Learning Improve Planning in LLM-based Agents?"
Awesome graph neural networks for brain network learning. Collections of related research papers with implementations, commonly used datasets and tools. We also invite researchers interested in brain...
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
PyTorch implementation of the Graph Attention Networks (GAT) based on the paper "Graph Attention Network" by Velickovic et al - https://arxiv.org/abs/1710.10903v3
[KDD'2024] "LLM4Graph: A Survey of Large Language Models for Graphs"
All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.
Segment Anything Model for large-scale, vectorized road network extraction from aerial imagery. CVPRW 2024
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Anomaly detection related books, papers, videos, and toolboxes
[KDD'2024] "LLM4Graph: A Survey of Large Language Models for Graphs"
"GraphEdit: Large Language Models for Graph Structure Learning"
[AAAI 2024] GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time
A Comprehensive Survey of Self-Supervised Learning for Recommendation