Követés
Peishi Jiang
Peishi Jiang
E-mail megerősítve itt: pnnl.gov
Cím
Hivatkozott rá
Hivatkozott rá
Év
A service-oriented architecture for coupling web service models using the Basic Model Interface (BMI)
P Jiang, M Elag, P Kumar, SD Peckham, L Marini, L Rui
Environmental Modelling & Software 92, 107-118, 2017
612017
Debates—Does information theory provide a new paradigm for Earth science? Causality, interaction, and feedback
AE Goodwell, P Jiang, BL Ruddell, P Kumar
Water Resources Research 56 (2), e2019WR024940, 2020
552020
Explore spatio‐temporal learning of large sample hydrology using graph neural networks
AY Sun, P Jiang, MK Mudunuru, X Chen
Water Resources Research 57 (12), e2021WR030394, 2021
372021
Digital Twin Earth--Coasts: Developing a fast and physics-informed surrogate model for coastal floods via neural operators
P Jiang, N Meinert, H Jordão, C Weisser, S Holgate, A Lavin, B Lütjens, ...
2021 NeurIPS Workshop on Machine Learning for the Physical Sciences (ML4PS), 2021
292021
Information transfer from causal history in complex system dynamics
P Jiang, P Kumar
Physical Review E 99 (1), 012306, 2019
262019
A graph neural network (GNN) approach to basin-scale river network learning: the role of physics-based connectivity and data fusion
AY Sun, P Jiang, ZL Yang, Y Xie, X Chen
Hydrology and Earth System Sciences 26 (19), 5163-5184, 2022
202022
Estimating watershed subsurface permeability from stream discharge data using deep neural networks
E Cromwell, P Shuai, P Jiang, ET Coon, SL Painter, JD Moulton, Y Lin, ...
Frontiers in Earth Science 9, 613011, 2021
172021
Establishing rainfall depth–duration–frequency relationships at daily raingauge stations in Hong Kong
P Jiang, YK Tung
Journal of hydrology 504, 80-93, 2013
162013
Using information flow for whole system understanding from component dynamics
P Jiang, P Kumar
Water Resources Research 55 (11), 8305-8329, 2019
142019
Interactions of information transfer along separable causal paths
P Jiang, P Kumar
Physical Review E 97 (4), 042310, 2018
132018
Using ensemble data assimilation to estimate transient hydrologic exchange flow under highly dynamic flow conditions
K Chen, X Chen, X Song, MA Briggs, P Jiang, P Shuai, G Hammond, ...
Water Resources Research 58 (5), e2021WR030735, 2022
122022
DART-PFLOTRAN: An ensemble-based data assimilation system for estimating subsurface flow and transport model parameters
P Jiang, X Chen, K Chen, J Anderson, N Collins, MEL Gharamti
Environmental Modelling & Software 142, 105074, 2021
72021
Incorporating daily rainfalls to derive rainfall DDF relationships at ungauged sites in Hong Kong and quantifying their uncertainty
P Jiang, YK Tung
Stochastic environmental research and risk assessment 29, 45-62, 2015
72015
Knowledge-informed deep learning for hydrological model calibration: An application to coal creek watershed in Colorado
P Jiang, P Shuai, A Sun, MK Mudunuru, X Chen
Hydrology and Earth System Sciences Discussions 2022, 1-31, 2022
62022
SWAT watershed model calibration using deep learning
MK Mudunuru, K Son, P Jiang, X Chen
arXiv preprint arXiv:2110.03097, 2021
62021
Bundled causal history interaction
P Jiang, P Kumar
Entropy 22 (3), 360, 2020
62020
Efficient Super‐Resolution of Near‐Surface Climate Modeling Using the Fourier Neural Operator
P Jiang, Z Yang, J Wang, C Huang, P Xue, TC Chakraborty, X Chen, ...
Journal of Advances in Modeling Earth Systems 15 (7), e2023MS003800, 2023
52023
Scalable deep learning for watershed model calibration
MK Mudunuru, K Son, P Jiang, G Hammond, X Chen
Frontiers in Earth Science 10, 1026479, 2022
32022
Using Mutual Information for Global Sensitivity Analysis on Watershed Modeling
P Jiang, K Son, MK Mudunuru, X Chen
Water Resources Research, e2022WR032932, 2022
32022
EdgeAI: How to use AI to collect reliable and relevant watershed data
MK Mudunuru, X Chen, S Karra, G Hammond, P Jiang, KC Solander, ...
Artificial Intelligence for Earth System Predictability (AI4ESP …, 2021
32021
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Cikkek 1–20