% Key papers for Neural combinatorial optimization on graphs (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_learning_56416,
  title = {{Learning Combinatorial Optimization Algorithms over Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9405},
}

@inproceedings{iclr2017_deep_28271,
  title = {{Deep Biaffine Attention for Neural Dependency Parsing}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=Hk95PK9le},
}

@inproceedings{neurips2019_exact_58228,
  title = {{Exact Combinatorial Optimization with Graph Convolutional Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14449},
}

@inproceedings{neurips2017_predicting_56587,
  title = {{Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9047},
}

@inproceedings{iclr2019_learning_28898,
  title = {{Learning a SAT Solver from Single-Bit Supervision}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/726},
}

@inproceedings{aaai2019_learning_101684,
  title = {{Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4399},
}

@inproceedings{icml2019_dag_37261,
  title = {{DAG-GNN: DAG Structure Learning with Graph Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4301},
}

@inproceedings{icml2018_learning_36802,
  title = {{Learning Steady-States of Iterative Algorithms over Graphs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2424},
}

@inproceedings{neurips2019_d_58074,
  title = {{D-VAE: A Variational Autoencoder for Directed Acyclic Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13371},
}

@inproceedings{neurips2017_premise_56592,
  title = {{Premise Selection for Theorem Proving by Deep Graph Embedding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9064},
}

@inproceedings{icml2017_decoupled_36129,
  title = {{Decoupled Neural Interfaces using Synthetic Gradients}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/665},
}

@inproceedings{aaai2020_accelerating_100635,
  title = {{Accelerating Primal Solution Findings for Mixed Integer Programs Based on Solution Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5503},
}

@inproceedings{icml2020_adaptive_37905,
  title = {{Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5900},
}

@inproceedings{cvpr2021_inferring_17186,
  title = {{Inferring CAD Modeling Sequences Using Zone Graphs}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2021_a_6,
  title = {{A Bottom-Up DAG Structure Extraction Model for Math Word Problems}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/00039-a-bottom-up-dag-structure-extraction-model-for-math-word-problems/},
}

@inproceedings{neurips2018_automatic_56882,
  title = {{Automatic differentiation in ML: Where we are and where we should be going}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11836},
}

@inproceedings{neurips2021_neurolkh_62364,
  title = {{NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28310},
}

@inproceedings{neurips2019_retrosynthesis_58912,
  title = {{Retrosynthesis Prediction with Conditional Graph Logic Network}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13939},
}

@inproceedings{cvpr2020_bundle_15215,
  title = {{Bundle Adjustment on a Graph Processor}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{iclr2020_reinforced_29864,
  title = {{Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=rkxDoJBYPB},
}

@inproceedings{aaai2024_learning_6507,
  title = {{Learning to Optimize Permutation Flow Shop Scheduling via Graph-Based Imitation Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29998},
}

@inproceedings{iclr2024_deep_35069,
  title = {{Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18004},
}

@inproceedings{neurips2024_a_71650,
  title = {{A Structure-Aware Framework for Learning Device Placements on Computation Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95628},
}

@inproceedings{aaai2026_learn_107299,
  title = {{Learn from Global Correlations: Enhancing Evolutionary Algorithm via Spectral GNN}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39651},
}

@inproceedings{iclr2024_improving_35403,
  title = {{Improving protein optimization with smoothed fitness landscapes}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17670},
}

@inproceedings{aaai2024_combhelper_5352,
  title = {{COMBHelper: A Neural Approach to Reduce Search Space for Graph Combinatorial Problems}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30070},
}

@inproceedings{aaai2024_end_5836,
  title = {{End-to-End Verification for Subgraph Solving}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28642},
}

@inproceedings{aaai2025_destroy_8704,
  title = {{Destroy and Repair Using Hyper-Graphs for Routing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34018},
}

@inproceedings{icml2024_surprisingly_43884,
  title = {{Surprisingly Strong Performance Prediction with Neural Graph Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34568},
}

@inproceedings{neurips2024_semantic_71579,
  title = {{Semantic Routing via Autoregressive Modeling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95691},
}

@inproceedings{aaai2025_learn2aggregate_9718,
  title = {{Learn2Aggregate: Supervised Generation of Chvatal-Gomory Cuts Using Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34900},
}

@inproceedings{aaai2025_neuro_10114,
  title = {{Neuro-Guided Graph Search for Symbolic Regression (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35314},
}

@inproceedings{iclr2024_constraint_34176,
  title = {{Constraint-Free Structure Learning with Smooth Acyclic Orientations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18899},
}

@inproceedings{icml2024_simulation_44756,
  title = {{Simulation of Graph Algorithms with Looped Transformers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33696},
}

@inproceedings{icml2025_g_48647,
  title = {{G-Adaptivity: optimised graph-based mesh relocation for finite element methods}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43974},
}

@inproceedings{neurips2024_deep_72276,
  title = {{Deep Equilibrium Algorithmic Reasoning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95069},
}

@inproceedings{neurips2024_graph_72568,
  title = {{Graph Learning for Numeric Planning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94804},
}

@inproceedings{iclr2026_frontierco_85189,
  title = {{FrontierCO: Real-World and Large-Scale Evaluation of Machine Learning Solvers for Combinatorial Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=BVprkacwFY},
}

@inproceedings{aaai2026_the_100004,
  title = {{The GATTACA Framework: Graph Neural Network-Based Reinforcement Learning for Controlling Biological Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37055},
}

@inproceedings{aaai2026_coco_107323,
  title = {{CoCo-MILP: Inter-Variable Contrastive and Intra-Constraint Competitive MILP Solution Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39675},
}