Alternatives and similar repositories for LOMAR

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

• Thinklab-SJTU / NAR-CO-Solver
  Official implementation non-autoregressive combinatorial optimizaiton solvers, covering our ICLR 2023 paper and SCIENTIA SINICA Informati…
  ☆41Updated last year
• ahottung / CVAE-Opt
  Learning a Latent Search Space for Routing Problems using Variational Autoencoders
  ☆28Updated 4 years ago
• JayMan91 / NeurIPSIntopt
  Implementation of "Interior Point Solving for LP-based prediction+optimisation" paper in Neurips 2020.
  ☆21Updated last year
• lyeskhalil / CORL
  ☆26Updated 3 years ago
• sanketkshah / LODLs
  Code for "Decision-Focused Learning without Differentiable Optimization: Learning Locally Optimized Decision Losses"
  ☆32Updated last year
• chaitjo / learning-paradigms-for-tsp
  Code for the paper 'On Learning Paradigms for the Travelling Salesman Problem' (NeurIPS 2019 Graph Representation Learning Workshop)
  ☆33Updated 5 years ago
• ZHANG-NI / AGFN
  ☆18Updated 3 months ago
• yudasong / Reinforcement-Learning-Branch-and-Bound
  ☆16Updated 7 years ago
• zdhNarsil / GFlowNet-CombOpt
  PyTorch implementation for our NeurIPS 2023 spotlight paper "Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with G…
  ☆66Updated 2 years ago
• Graph-COM / Meta_CO
  the official repository of the paper unsupervised learning for combinatorial optimization needs meta learning
  ☆10Updated 2 years ago
• Baijiong-Lin / MOML
  [NeurIPS 2021 | AIJ 2024] Multi-Objective Meta Learning
  ☆17Updated last year
• ruchtem / cosmos
  This is the official implementation for COSMOS: a method to learn Pareto fronts that scales to large datasets and deep models.
  ☆39Updated 4 years ago
• thanhnguyentang / offline_neural_bandits
  An official JAX-based code for our NeuraLCB paper, "Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization", ICLR…
  ☆13Updated 3 years ago
• LOGO-CUHKSZ / ASP
  ☆23Updated last year
• VITA-Group / L2O-Training-Techniques
  [NeurIPS 2020 Spotlight Oral] "Training Stronger Baselines for Learning to Optimize", Tianlong Chen*, Weiyi Zhang*, Jingyang Zhou, Shiyu …
  ☆29Updated 4 years ago
• DIMESTeam / DIMES
  ☆46Updated 8 months ago
• Stalence / erdos_neu
  Official Repo for the NeurIPS2020 paper "Erdos Goes Neural: An Unsupervised Learning Framework for Combinatorial Optimization on Graphs"
  ☆51Updated 3 years ago
• aurelienbibaut / DQN_MVC
  Implementation of Learning Combinatorial Optimization Algorithms over Graphs, by Hanjun Dai et al. (2017)
  ☆34Updated 8 years ago
• nik7273 / covid-pgmorl
  Multi-objective reinforcement learning for covid-19 control
  ☆12Updated 4 years ago
• davidireland-iso / LeNSE
  ☆14Updated 3 years ago
• michaelzcjia / smart_predict_optimize
  MIE424 Group Project: smart_predict_optimize
  ☆15Updated 4 years ago
• weiyu123112 / City-Metro-Network-Expansion-with-RL
  City Metro Network Expansion with Reinforcement Learning
  ☆12Updated 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 2 years ago
• Elizabethxyhu / NeurIPS_Two_Stage_Predict-Optimize
  ☆26Updated 2 years ago
• qiang-ma / HRL-for-combinatorial-optimization
  Hierarchical deep reinforcement learning for combinatorial optimization problem
  ☆35Updated 6 years ago
• daizhongxiang / Federated_Bayesian_Optimization
  Code for the NeurIPS 2020 paper: "Federated Bayesian Optimization via Thompson Sampling"
  ☆26Updated 5 years ago
• xyfffff / rethink_mcts_for_tsp
  [ICML'24 Oral] Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
  ☆40Updated 9 months ago
• Bill-CJB / NHDE
  ☆27Updated 2 years ago
• BUAA-BDA / SpatialCrowdsourcing-GOMA
  GOMA is a two-sided online task assignment problem in Spatial Crowdsourcing.
  ☆19Updated 2 years ago
• idea-iitd / GCOMB
  ☆36Updated 2 years ago