% Key papers for Scalable approximation and equivariant compute (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2022_mace_65239,
  title = {{MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53926},
}

@inproceedings{icml2018_adafactor_36495,
  title = {{Adafactor: Adaptive Learning Rates with Sublinear Memory Cost}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2446},
}

@inproceedings{iclr2018_a_28622,
  title = {{A Scalable Laplace Approximation for Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/224},
}

@inproceedings{iclr2024_equiformerv2_35170,
  title = {{EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17903},
}

@inproceedings{neurips2025_uma_77357,
  title = {{UMA: A Family of Universal Models for Atoms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=SvopaNxYWt},
}

@inproceedings{cvpr2016_tensr_11916,
  title = {{TenSR: Multi-Dimensional Tensor Sparse Representation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{neurips2018_simple_57626,
  title = {{Simple, Distributed, and Accelerated Probabilistic Programming}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11730},
}

@inproceedings{cvpr2023_pypose_21948,
  title = {{PyPose: A Library for Robot Learning With Physics-Based Optimization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22336},
}

@inproceedings{neurips2019_anodev2_57857,
  title = {{ANODEV2: A Coupled Neural ODE Framework}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13657},
}

@inproceedings{neurips2023_separable_68815,
  title = {{Separable Physics-Informed Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71036},
}

@inproceedings{cvpr2019_eigen_14124,
  title = {{EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching From Scratch}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{aaai2023_sci_4571,
  title = {{SCI: A Spectrum Concentrated Implicit Neural Compression for Biomedical Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25602},
}

@inproceedings{aaai2021_efficient_502,
  title = {{Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/07583-efficient-on-chip-learning-for-optical-neural-networks-through-power-aware-sparse-zeroth-order-optimization/},
}

@inproceedings{neurips2018_tangent_57675,
  title = {{Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11606},
}

@inproceedings{neurips2020_autoprivacy_59406,
  title = {{AutoPrivacy: Automated Layer-wise Parameter Selection for Secure Neural Network Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17254},
}

@inproceedings{neurips2023_tensornet_67216,
  title = {{TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72498},
}

@inproceedings{icml2020_t_38826,
  title = {{T-Basis: a Compact Representation for Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6594},
}

@inproceedings{aaai2025_powermlp_10334,
  title = {{PowerMLP: An Efficient Version of KAN}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34210},
}

@inproceedings{cvpr2023_transformer_22413,
  title = {{Transformer-Based Learned Optimization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21448},
}

@inproceedings{neurips2021_tenset_62615,
  title = {{TenSet: A Large-scale Program Performance Dataset for Learned Tensor Compilers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://openreview.net/forum?id=aIfp8kLuvc9},
}

@inproceedings{aaai2024_inducing_6319,
  title = {{Inducing Point Operator Transformer: A Flexible and Scalable Architecture for Solving PDEs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27766},
}

@inproceedings{iclr2025_towards_80572,
  title = {{Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy Hessians}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31192},
}

@inproceedings{iclr2024_kw_35192,
  title = {{KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17881},
}

@inproceedings{neurips2024_multiple_71127,
  title = {{Multiple Physics Pretraining for Spatiotemporal Surrogate Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96095},
}

@inproceedings{neurips2024_the_72662,
  title = {{The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94722},
}

@inproceedings{aaai2025_scalable_10677,
  title = {{Scalable Quantum-Inspired Optimization Through Dynamic Qubit Compression}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33235},
}

@inproceedings{neurips2024_matformer_73238,
  title = {{MatFormer: Nested Transformer for Elastic Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94199},
}

@inproceedings{neurips2024_kronecker_73546,
  title = {{Kronecker-Factored Approximate Curvature for Physics-Informed Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93933},
}

@inproceedings{iclr2026_distmlip_84633,
  title = {{DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=4tasfBIPxp},
}

@inproceedings{neurips2024_quantum_71072,
  title = {{Quantum Deep Equilibrium Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96140},
}

@inproceedings{neurips2024_amortized_71948,
  title = {{Amortized Eigendecomposition for Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95360},
}

@inproceedings{neurips2025_generalizable_74839,
  title = {{Generalizable, real-time neural decoding with hybrid state-space models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=1i4wNFgHDd},
}

@inproceedings{aaai2024_quantum_7044,
  title = {{Quantum-Inspired Neural Network with Runge-Kutta Method}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29753},
}

@inproceedings{icml2024_scaling_43720,
  title = {{Scaling Tractable Probabilistic Circuits: A Systems Perspective}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34732},
}

@inproceedings{neurips2024_what_70458,
  title = {{What is my quantum computer good for? Quantum capability learning with physics-aware neural networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96649},
}

@inproceedings{neurips2025_venus_80099,
  title = {{Venus-MAXWELL: Efficient Learning of Protein-Mutation Stability Landscapes using Protein Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=w7hiWakSAq},
}

@inproceedings{neurips2025_titan_80147,
  title = {{TITAN: A Trajectory-Informed Technique for Adaptive Parameter Freezing in Large-Scale VQE}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=weU95NZePs},
}