Seuraa
Rui Wang
Nimike
Viittaukset
Viittaukset
Vuosi
Towards physics-informed deep learning for turbulent flow prediction
R Wang, K Kashinath, M Mustafa, A Albert, R Yu
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
3462020
Physics-informed machine learning: case studies for weather and climate modelling
K Kashinath, M Mustafa, A Albert, JL Wu, C Jiang, S Esmaeilzadeh, ...
Philosophical Transactions of the Royal Society A 379 (2194), 20200093, 2021
3252021
Incorporating symmetry into deep dynamics models for improved generalization
R Wang, R Walters, R Yu
International Conference on Learning Representations (ICLR), 2021
1492021
Physics-guided deep learning for dynamical systems: A survey
R Wang, R Yu
arXiv preprint arXiv:2107.01272, 2021
642021
Approximately Equivariant Networks for Imperfectly Symmetric Dynamics
R Wang, R Walters, R Yu
International Conference on Machine Learning (ICML), 2022
512022
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems
R Wang, D Maddix, C Faloutsos, Y Wang, R Yu
Learning for Dynamics and Control, 385-398, 2021
452021
Artificial intelligence for science in quantum, atomistic, and continuum systems
X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie, M Liu, Y Lin, Z Xu, K Yan, ...
arXiv preprint arXiv:2307.08423, 2023
422023
Prediction of Alzheimer’s disease-associated genes by integration of GWAS summary data and expression data
S Hao, R Wang, Y Zhang, H Zhan
Frontiers in genetics 9, 653, 2019
382019
Meta-learning dynamics forecasting using task inference
R Wang, R Walters, R Yu
Advances in Neural Information Processing Systems 35, 21640-21653, 2022
262022
Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts
R Wang, Y Dong, SO Arik, R Yu
The Eleventh International Conference on Learning Representations, 2023
15*2023
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting
R Wang, R Walters, R Yu
International Conference on Machine Learning (ICML) Principles of …, 2022
92022
Aortic Pressure Forecasting with Deep Learning
E Huang, R Wang, U Chandrasekaran, R Yu
2020 Computing in Cardiology, 2020
6*2020
Learning Dynamical Systems Requires Rethinking Generalization
R Wang, D Maddix, C Faloutsos, Y Wang, R Yu
32020
Physics-guided deep learning for spatiotemporal forecasting
R Wang, R Walters, R Yu
Knowledge Guided Machine Learning, 179-210, 2022
12022
Left ventricular volume and cardiac output estimation using machine learning model
A El Katerji, Q Tan, E Kroeker, R Wang
US Patent App. 18/143,630, 2024
2024
Relaxed Octahedral Group Convolution for Learning Symmetry Breaking in 3D Physical Systems
R Wang, G Han, R Walters, TE Smidt
arXiv preprint arXiv:2310.02299, 2023
2023
Intra-aortic pressure forecasting
A El Katerji, E Kroeker, E Jortberg, R Yu, R Wang
US Patent App. 18/096,589, 2023
2023
Left ventricular volume and cardiac output estimation using machine learning model
A El Katerji, Q Tan, E Kroeker, R Wang
US Patent 11,694,813, 2023
2023
Intra-aortic pressure forecasting
A El Katerji, E Kroeker, E Jortberg, R Yu, R Wang
US Patent 11,581,083, 2023
2023
Physics-Guided Deep Learning for Dynamics Forecasting
R Wang
University of California, San Diego, 2023
2023
Järjestelmä ei voi suorittaa toimenpidettä nyt. Yritä myöhemmin uudelleen.
Artikkelit 1–20