% Key papers for Physics-informed neural network training (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2021_characterizing_62607,
  title = {{Characterizing possible failure modes in physics-informed neural networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26497},
}

@inproceedings{aaai2021_dpm_356,
  title = {{DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08146-dpm-a-novel-training-method-for-physics-informed-neural-networks-in-extrapolation/},
}

@inproceedings{aaai2022_spline_2771,
  title = {{Spline-PINN: Approaching PDEs without Data Using Fast, Physics-Informed Hermite-Spline CNNs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/08529-spline-pinn-approaching-pdes-without-data-using-fast-physics-informed-hermite-spline-cnns/},
}

@inproceedings{icml2024_challenges_45272,
  title = {{Challenges in Training PINNs: A Loss Landscape Perspective}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33180},
}

@inproceedings{neurips2024_pinnacle_72866,
  title = {{PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97621},
}

@inproceedings{iclr2024_pinnsformer_33933,
  title = {{PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19142},
}

@inproceedings{neurips2022_generic_65424,
  title = {{Generic bounds on the approximation error for physics-informed (and) operator learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54367},
}

@inproceedings{neurips2022_is_65487,
  title = {{Is \$L^2\$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55104},
}

@inproceedings{neurips2022_accelerated_64755,
  title = {{Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53689},
}

@inproceedings{neurips2025_gradient_78851,
  title = {{Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=iweeVl1RHU},
}

@inproceedings{iclr2023_competitive_33425,
  title = {{Competitive Physics Informed Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/10870},
}

@inproceedings{aaai2023_pixel_4333,
  title = {{PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25988},
}

@inproceedings{icml2023_multiadam_42880,
  title = {{MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23480},
}

@inproceedings{neurips2023_hypernetwork_68867,
  title = {{Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70991},
}

@inproceedings{icml2024_parameterized_45311,
  title = {{Parameterized Physics-informed Neural Networks for Parameterized PDEs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33141},
}

@inproceedings{neurips2024_ropinn_74427,
  title = {{RoPINN: Region Optimized Physics-Informed Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93144},
}

@inproceedings{iclr2024_an_34601,
  title = {{An operator preconditioning perspective on training in physics-informed machine learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18473},
}

@inproceedings{iclr2024_scaling_35483,
  title = {{Scaling physics-informed hard constraints with mixture-of-experts}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17590},
}

@inproceedings{aaai2025_number_10136,
  title = {{Number Theoretic Accelerated Learning of Physics-Informed Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32040},
}

@inproceedings{iclr2023_bi_33084,
  title = {{Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11901},
}

@inproceedings{neurips2025_fp64_74927,
  title = {{FP64 is All You Need: Rethinking Failure Modes in Physics-Informed Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=2aotKzkOCm},
}

@inproceedings{iclr2025_config_81136,
  title = {{ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30634},
}

@inproceedings{iclr2026_fast_84516,
  title = {{Fast training of accurate physics-informed neural networks without gradient descent}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=3VdSuh3sie},
}

@inproceedings{iclr2024_solving_35321,
  title = {{Solving High Frequency and Multi-Scale PDEs with Gaussian Processes}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17752},
}

@inproceedings{icml2024_learning_45118,
  title = {{Learning from Integral Losses in Physics Informed Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33334},
}

@inproceedings{icml2025_sub_47517,
  title = {{Sub-Sequential Physics-Informed Learning with State Space Model}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45079},
}

@inproceedings{neurips2025_hybrid_76535,
  title = {{Hybrid Boundary Physics-Informed Neural Networks for Solving Navier-Stokes Equations with Complex Boundary}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=KQoVgPOM1S},
}

@inproceedings{neurips2026_coupled_90077,
  title = {{Coupled Integral PINN for Discontinuity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153205},
}

@inproceedings{aaai2026_physics_107069,
  title = {{Physics-Informed Approach for Exploratory Hamilton–Jacobi–Bellman Equations via Policy Iterations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39421},
}

@inproceedings{aaai2026_a_107548,
  title = {{A Multi-Objective Optimization Framework for Adaptive Weighting in Physics-Informed Machine Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39900},
}

@inproceedings{icml2024_efficient_43493,
  title = {{Efficient Error Certification for Physics-Informed Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34959},
}