A real-world dataset for EV-related research, e.g., spatiotemporal prediction and urban energy management.
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Updated
Oct 24, 2024 - Python
A real-world dataset for EV-related research, e.g., spatiotemporal prediction and urban energy management.
GPU-accelerated Next-Generation Network Analytics and Graph Learning for Time Series Data on Complex Networks.
Welcome to the Graph Neural Networks (06838-01) class repository for the Department of Artificial Intelligence at the Catholic University of Korea. This platform is dedicated to sharing and archiving lecture materials such as practices, assignments, and sample codes for the class.
Interesting papers related to graph data mining. (published on ICML, IJCAI, KDD 2024... )
[NeurIPS 2024] Official implementation for paper "Can Graph Learning Improve Planning in LLM-based Agents?"
[EMNLP'2024] "OpenGraph: Towards Open Graph Foundation Models"
Extensible Surrogate Potential of Ab initio Learned and Optimized by Message-passing Algorithm 🍹https://arxiv.org/abs/2010.01196
[ICLR 2024] "Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel"
Neuro-symbolic interpretation learning (mostly just language-learning, for now)
Bayesian survival models for high-dimensional data
Advances on machine learning of graphs, covering the reading list of recent top academic conferences.
"AnyGraph: Graph Foundation Model in the Wild"
Paper List for Fair Graph Learning (FairGL).
[ICDE'2024] "GraphAug: Graph Augmentation for Recommendation"
Hop-Wise Graph Attention for Scalable and Generalizable Learning on Circuits
Work we did for a practical course in graph learning, organized by department Informatik 7 at RWTH University
Codes and data for KDD 2024 Research Track paper "ProCom: A Few-shot Targeted Community Detection Algorithm"
Graph Optimiser for Learning and Evolution of Models
Weisfeiler Lehman Coloring algorithm is a benchmark in Graph isomorphism Testing. Infact, it bounds the expressive power of GNNs. This is a python impelementation of 1-WL test.
Code for the paper "PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks" (ICPR 2020)
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