Starred repositories
This repository contains the source code used in the computational experiments of the paper: Learning to Solve Bilevel Programs with Binary Tender (ICLR 2024, available on OpenReview.net).
PPO implementation of the DRL agent used in the paper "Deep Reinforcement Learning meets Graph Neural Networks: exploring a routing optimization use case"
Implementation of "Learning Combinatorial Optimization Algorithms over Graphs"
A PyTorch implementation of ACM SIGKDD 2019 paper "Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks"
Some GNNs are implemented using PyG for node classification tasks, including: GCN, GraphSAGE, SGC, GAT, R-GCN and HAN (Heterogeneous Graph Attention Network), which will continue to be updated in t…
Codes, instances and numerical results for the bilevel discrete network design problem (DNDP).
Deep reinforcement learning for mobile edge computing
This is the repository for the collection of Graph-based Deep Learning for Communication Networks.
The official repository for the paper "Deep learning for dynamic graphs: models and benchmarks" accepted at IEEE TNNLS
WarAgent: LLM-based Multi-Agent Simulation of World Wars
PyTorch Tutorial for Deep Learning Researchers
This is the code for paper "Scalable Resource Management for Dynamic MEC: An Unsupervised Link-Output Graph Neural Network Approach"
SEAL (learning from Subgraphs, Embeddings, and Attributes for Link prediction). "M. Zhang, Y. Chen, Link Prediction Based on Graph Neural Networks, NeurIPS 2018 spotlight".
Inductive graph-based matrix completion (IGMC) from "M. Zhang and Y. Chen, Inductive Matrix Completion Based on Graph Neural Networks, ICLR 2020 spotlight".
Exact Combinatorial Optimization with Graph Convolutional Neural Networks (NeurIPS 2019)
Pytorch implementation of a dynamic gnn based on Roland framework
Graph Neural Network Library for PyTorch
Extensible Combinatorial Optimization Learning Environments
Predict and search framework for MilP
Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs).
The source code of 《Large AI Model-Based Semantic Communications》