Alternatives and similar repositories for GCOMB

Users that are interested in GCOMB are comparing it to the libraries listed below

• Stalence / erdos_neu
  Official Repo for the NeurIPS2020 paper "Erdos Goes Neural: An Unsupervised Learning Framework for Combinatorial Optimization on Graphs"
  ☆49Updated 3 years ago
• tomdbar / eco-dqn
  Implementation of ECO-DQN as reported in "Exploratory Combinatorial Optimization with Reinforcement Learning".
  ☆80Updated 4 years ago
• louisv123 / COLGE
  ☆37Updated 6 years ago
• SunQingYun1996 / Graph-Reinforcement-Learning-Papers
  A curated list of graph reinforcement learning papers.
  ☆72Updated 3 years ago
• aurelienbibaut / DQN_MVC
  Implementation of Learning Combinatorial Optimization Algorithms over Graphs, by Hanjun Dai et al. (2017)
  ☆33Updated 7 years ago
• kage08 / graph_sample_rl
  Influence maximization in unknown social networks: Learning Policies for Effective Graph Sampling (official code repository)
  ☆29Updated 3 years ago
• MaxiBoether / mis-benchmark-framework
  A benchmarking suite for maximum independent set solvers.
  ☆51Updated last year
• ShengdingHu / GraphPolicyNetworkActiveLearning
  The source code for NeurIPS 2020 paper "Graph Policy Network for Transferable Active Learning on Graphs"
  ☆46Updated 4 years ago
• machine-reasoning-ufrgs / TSP-GNN
  Graph Neural Network architecture to solve the decision variant of the Traveling Salesperson Problem (is there a Hamiltonian tour in G wi…
  ☆117Updated 5 years ago
• triplej0079 / DeepIM
  ☆45Updated 2 years ago
• neunms / Reinforcement-learning-on-graphs-A-survey
  This collection of papers can be used to summarize research about graph reinforcement learning for the convenience of researchers.
  ☆189Updated 9 months ago
• Thinklab-SJTU / PPO-BiHyb
  Implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs".
  ☆100Updated 2 years ago
• wondergo2017 / TSP-HAC
  Codes for AAAI22 paper "Learning to Solve Travelling Salesman Problem with Hardness-Adaptive Curriculum"
  ☆22Updated 3 years ago
• zdhNarsil / GFlowNet-CombOpt
  PyTorch implementation for our NeurIPS 2023 spotlight paper "Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with G…
  ☆67Updated 2 years ago
• qiang-ma / graph-pointer-network
  ☆163Updated 5 years ago
• VGraphRNN / VGRNN
  Variational Graph Recurrent Neural Networks - PyTorch
  ☆116Updated 5 years ago
• DIMESTeam / DIMES
  ☆42Updated 3 months ago
• vthost / DAGNN
  A graph neural network tailored to directed acyclic graphs that outperforms conventional GNNs by leveraging the partial order as strong i…
  ☆134Updated last year
• ahottung / CVAE-Opt
  Learning a Latent Search Space for Routing Problems using Variational Autoencoders
  ☆26Updated 4 years ago
• tomdbar / ecord
  Supporting code for "Learning to Solve Combinatorial Graph Partitioning Problems via Efficient Exploration".
  ☆14Updated 3 years ago
• isl-org / NPHard
  Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
  ☆154Updated 11 months ago
• FFrankyy / FINDER
  FINDER - FInding key players in complex Networks through DEep Reinforcement learning (Nature Machine Intelligence)
  ☆205Updated 2 years ago
• Dtrycode / ToupleGDD
  Implementation of "ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning" (https://arxiv.org/abs/2…
  ☆29Updated 2 years ago
• facebookresearch / neural-rewriter
  Learning to Perform Local Rewriting for Combinatorial Optimization
  ☆151Updated 5 years ago
• flyingtango / DiGCN
  Implement of DiGCN, NeurIPS-2020
  ☆47Updated 4 years ago
• uoguelph-mlrg / LDG
  PyTorch code for "Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions"
  ☆101Updated 4 years ago
• Graph-COM / CO_ProxyDesign
  The repository for 'Unsupervised Learning for Combinatorial Optimization with Principled Proxy Design'
  ☆16Updated 2 years ago
• lyeskhalil / CORL
  ☆25Updated 3 years ago
• hanxiongwei / L2O-Solver-Papers
  ☆11Updated 5 years ago
• kaist-silab / meta-sage
  [ICML 2023] Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial Optim…
  ☆10Updated last year