This is the repository for the collection of Graph-based Deep Learning for Communication Networks.
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Updated
Jun 5, 2024
This is the repository for the collection of Graph-based Deep Learning for Communication Networks.
A Python package housing a collection of deep-learning multi-modal data fusion method pipelines! From data loading, to training, to evaluation - fusilli's got you covered 🌸
Graph Neural Network based Social Recommendation Model. SIGIR2019.
GFlowNet library specialized for graph & molecular data
A Deep learning library for neutrino telescopes
Multi-task learning using message passing graph neural network for radar based perception functions
Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs).
ReOnto is a neuro-symbolic approach where we use ontologies and GNNs to extract relations from sentences.
This repository includes files of work for Suicidal Ideation detection based on social media dataset using semantic, contextual and graph neural network based hybrid approach
DiTEC research
Implementation for "Global heterogeneous graph convolutional network: from coarse to refined land cover and land use segmentation"
hypergraph representation learning, graph neural network
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections, ICLR 2024
A knowledge graph system with graph neural network for drug repurposing and disease mechanism.
scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks
polyGNN is a Python library to automate ML model training for polymer informatics.
Quick and simple Deep Learning projects for learning and experimenting. Ideal for beginners and those looking to practice AI concepts.
GNN trained on the ZINC dataset (graph-level regression)
A library for graph deep learning research
CRSLab is an open-source toolkit for building Conversational Recommender System (CRS).
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