Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks
Authors: Woojin Cho, Kookjin Lee, Donsub Rim, Noseong Park
NeurIPS 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 4 Experiments We demonstrate that our proposed method significantly outperforms baselines on the 1-dimensional/2dimensional PDE benchmarks that are known to be very challenging for PINNs to learn [17, 18]. |
| Researcher Affiliation | Academia | Woojin Cho Kookjin Lee Donsub Rim Noseong Park Yonsei University Arizona State University Washington University in St. Louis snowmoon@yonsei.ac.kr, kookjin.lee@asu.edu, rim@wustl.edu, noseong@yonsei.ac.kr |
| Pseudocode | No | The paper mentions 'See Appendix E for the formal algorithm' but Appendix E is not provided in the current document. No pseudocode or algorithm blocks are present in the main body. |
| Open Source Code | No | The paper refers to 'Appendix F, including hyperparameter configuration and software/hardware environments' for reproducibility, but does not provide an explicit statement about open-source code release or a link to a repository for the described methodology. |
| Open Datasets | No | The paper describes solving partial differential equations (PDEs) by training on generated collocation points, rather than using a publicly available dataset with specific access information. |
| Dataset Splits | No | The paper describes a two-phase training process (Phase 1 for meta-learning, Phase 2 for fine-tuning on test PDE parameters) and uses 'test collocation points' for evaluation, but does not specify distinct training, validation, and test dataset splits with percentages or counts. |
| Hardware Specification | No | The paper mentions 'Appendix F, including hyperparameter configuration and software/hardware environments' for reproducibility, but Appendix F is not provided in the current document, and no specific hardware details are mentioned elsewhere. |
| Software Dependencies | No | The paper mentions 'Appendix F, including hyperparameter configuration and software/hardware environments' for reproducibility, but Appendix F is not provided in the current document, and no specific software dependencies with version numbers are mentioned elsewhere. |
| Experiment Setup | No | The paper refers to 'Appendix F, including hyperparameter configuration and software/hardware environments' for reproducibility, but Appendix F is not provided in the current document, and no specific experimental setup details or hyperparameter values are mentioned elsewhere. |