| Hypernetwork-based meta-learning for low-rank physics-informed neural networks W Cho, K Lee, D Rim, N Park Advances in Neural Information Processing Systems 36, 11219-11231, 2023 | 21 | 2023 |
| Parameterized physics-informed neural networks for parameterized PDEs W Cho, M Jo, H Lim, K Lee, D Lee, S Hong, N Park arXiv preprint arXiv:2408.09446, 2024 | 15 | 2024 |
| Learning flexible body collision dynamics with hierarchical contact mesh transformer YY Yu, J Choi, W Cho, K Lee, N Kim, K Chang, CS Woo, I Kim, SW Lee, ... arXiv preprint arXiv:2312.12467, 2023 | 7 | 2023 |
| Operator-learning-inspired modeling of neural ordinary differential equations W Cho, S Cho, H Jin, J Jeon, K Lee, S Hong, D Lee, J Choi, N Park Proceedings of the AAAI Conference on Artificial Intelligence 38 (10), 11543 …, 2024 | 2 | 2024 |
| Extension of Physics-informed Neural Networks to Solving Parameterized PDEs W Cho, M Jo, H Lim, K Lee, D Lee, S Hong, N Park ICLR 2024 Workshop on AI4DifferentialEquations In Science, 2024 | 1 | 2024 |
| When Neural ODEs meet Neural Operators W Cho, S Cho, H Jin, J Jeon, K Lee, S Hong, D Lee, J Choi, N Park | 1 | 2022 |
| FastLRNR and Sparse Physics Informed Backpropagation W Cho, K Lee, N Park, D Rim, G Welper Results in Applied Mathematics 25, 100547, 2025 | | 2025 |
| Identifying Contemporaneous and Lagged Dependence Structures by Promoting Sparsity in Continuous-time Neural Networks F Wu, W Cho, D Korotky, S Hong, D Rim, N Park, K Lee Proceedings of the 33rd ACM International Conference on Information and …, 2024 | | 2024 |
| MaD-Scientist: AI-based Scientist solving Convection-Diffusion-Reaction Equations Using Massive PINN-Based Prior Data M Kang, D Lee, W Cho, J Park, K Lee, A Gruber, Y Hong, N Park arXiv preprint arXiv:2410.06442, 2024 | | 2024 |
| Extension of Physics-informed Neural Networks to Solving Parameterized PDEs N Park, W Cho, M Jo, H Lim, K Lee, D Lee, S Hong ICLR 2024, 2024 | | 2024 |
| Parameterized Physics-informed Neural Networks for Parameterized PDEs N Park, W Cho, M Jo, H Lim, K Lee, D Lee, S Hong International Conference on Machine Learning (ICML 2024), 2024 | | 2024 |
| Neural Functions for Learning Periodic Signal W Cho, M Jo, K Lee, N Park The Thirteenth International Conference on Learning Representations, 0 | | |
| Neural Compression for Multispectral Satellite Images W Cho, SA Immanuel, J Heo, D Kwon Workshop on Machine Learning and Compression, NeurIPS 2024, 0 | | |
| Can we pre-train ICL-based SFMs for the zero-shot inference of the 1D CDR problem with noisy data? M Kang, D Lee, W Cho, K Lee, A Gruber, N Trask, Y Hong, N Park Neurips 2024 Workshop Foundation Models for Science: Progress, Opportunities …, 0 | | |
| Promoting Sparsity in Continuous-time Neural Networks to Learn Dependence Structures F Wu, W Cho, D Korotky, S Hong, D Rim, N Park, K Lee | | |
| NeRT: Implicit Neural Representation for Time Series W Cho, M Jo, K Lee, N Park | | |
Noseong ParkTenured Associate Professor, KAISTยืนยันอีเมลแล้วที่ kaist.ac.kr