Adaptive mesh refinement based on high order finite difference WENO scheme for multi-scale simulations. - Chaopeng Shen; Jing-Mei Qiu; Andrew J. Christlieb (J. Comput. Phys., 2011)

High-Resolution Simulation of Pore-Scale Reactive Transport Processes Associated with Carbon Sequestration. - David Trebotich; Mark F. Adams; Sergi Molins; Carl I. Steefel; Chaopeng Shen (Comput. Sci. Eng., 2014)

Quantifying the effects of data integration algorithms on the outcomes of a subsurface-land surface processes model. - Chaopeng Shen; Jie Niu; Kuai Fang (Environ. Model. Softw., 2014)

A Novel Filtering Method for Infrared Image. - Jian Kang; Chunxiao Zhou; Weiqiang Xia; Chaopeng Shen; Guanglu Sun (ICYCSEE (1), 2016)

A trans-disciplinary review of deep learning research for water resources scientists. - Chaopeng Shen (CoRR, 2017)

The introspective may achieve more: Enhancing existing Geoscientific models with native-language emulated structural reflection. - Xinye Ji; Chaopeng Shen (Comput. Geosci., 2018)

An FPGA Design and Implementation of 4G Network Security Algorithm Based on SNOW3G. - Chaopeng Shen; Xiaotao Yan; Qiaozhen Liu; Jian Kang; Yang Liu; Xiaogang Zheng; Xige Zhang; Yuanyi Liu (QRS Companion, 2019)

Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions. - Kuai Fang; Chaopeng Shen; Daniel Kifer (CoRR, 2019)

Enhancing streamflow forecast and extracting insights using long-short term memory networks with data integration at continental scales. - Dapeng Feng; Kuai Fang; Chaopeng Shen (CoRR, 2019)

The Value of SMAP for Long-Term Soil Moisture Estimation With the Help of Deep Learning. - Kuai Fang; Ming Pan; Chaopeng Shen (IEEE Trans. Geosci. Remote. Sens., 2019)

From parameter calibration to parameter learning: Revolutionizing large-scale geoscientific modeling with big data. - Wen-Ping Tsai; Ming Pan; Kathryn Lawson; Jiangtao Liu; Dapeng Feng; Chaopeng Shen (CoRR, 2020)

Prediction in ungauged regions with sparse flow duration curves and input-selection ensemble modeling. - Dapeng Feng; Kathryn Lawson; Chaopeng Shen (CoRR, 2020)

The data synergy effects of time-series deep learning models in hydrology. - Kuai Fang; Daniel Kifer; Kathryn Lawson; Dapeng Feng; Chaopeng Shen (CoRR, 2021)

Continental-scale streamflow modeling of basins with reservoirs: a demonstration of effectiveness and a delineation of challenges. - Wenyu Ouyang; Kathryn Lawson; Dapeng Feng; Lei Ye; Chi Zhang; Chaopeng Shen (CoRR, 2021)

Surrogate Model for Shallow Water Equations Solvers with Deep Learning. - Yalan Song; Chaopeng Shen; Xiaofeng Liu (CoRR, 2021)

Bathymetry Inversion using a Deep-Learning-Based Surrogate for Shallow Water Equations Solvers. - Xiaofeng Liu; Yalan Song; Chaopeng Shen (CoRR, 2022)

Differentiable, learnable, regionalized process-based models with physical outputs can approach state-of-the-art hydrologic prediction accuracy. - Dapeng Feng; Jiangtao Liu; Kathryn Lawson; Chaopeng Shen (CoRR, 2022)

ThreshNet: Segmentation Refinement Inspired by Region-Specific Thresholding. - Savinay Nagendra; Chaopeng Shen; Daniel Kifer (CoRR, 2022)

Constructing a Large-Scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates. - Savinay Nagendra; Daniel Kifer; Benjamin Mirus; Te Pei; Kathryn Lawson; Srikanth Banagere Manjunatha; Weixin Li; Hien Nguyen 003; Tong Qiu; Sarah Tran; Chaopeng Shen (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

Integration of Multisource Data to Estimate Downward Longwave Radiation Based on Deep Neural Networks. - Fuxin Zhu; Xin Li 029; Jun Qin; Kun Yang 004; Lan Cuo; Wenjun Tang; Chaopeng Shen (IEEE Trans. Geosci. Remote. Sens., 2022)

Differentiable modeling to unify machine learning and physical models and advance Geosciences. - Chaopeng Shen; Alison P. Appling; Pierre Gentine; Toshiyuki Bandai; Hoshin V. Gupta; Alexandre Tartakovsky; Marco Baity-Jesi; Fabrizio Fenicia; Daniel Kifer; Li Li; Xiaofeng Liu; Wei Ren; et al. (CoRR, 2023)

Probing the limit of hydrologic predictability with the Transformer network. - Jiangtao Liu; Yuchen Bian; Chaopeng Shen (CoRR, 2023)

Estimating Uncertainty in Landslide Segmentation Models. - Savinay Nagendra; Chaopeng Shen; Daniel Kifer (CoRR, 2023)

The geometry of flow: Advancing predictions of river geometry with multi-model machine learning. - Shuyu Y. Chang; Zahra Ghahremani; Laura Manuel; Seyed Mohammad Hassan Erfani; Chaopeng Shen; Sagy Cohen; Kimberly Van Meter; Jennifer L. Pierce; Ehab A Meselhe; Erfan Goharian (CoRR, 2023)

SAMIC: Segment Anything with In-Context Spatial Prompt Engineering. - Savinay Nagendra; Kashif Rashid; Chaopeng Shen; Daniel Kifer (CoRR, 2024)

Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations. - Abdolmehdi Behroozi; Chaopeng Shen; Daniel Kifer (ICLR, 2025)

Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models. - Amirmoez Jamaat; Yalan Song; Farshid Rahmani; Jiangtao Liu; Kathryn Lawson; Chaopeng Shen (CoRR, 2025)

Distinct hydrologic response patterns and trends worldwide revealed by physics-embedded learning. - Haoyu Ji; Yalan Song; Tadd Bindas; Chaopeng Shen; Yuan Yang; Ming Pan; Jiangtao Liu; Farshid Rahmani; Ather Abbas; Hylke E. Beck; Kathryn Lawson; Yoshihide Wada (CoRR, 2025)

Bayesian Deep Learning for Convective Initiation Nowcasting Uncertainty Estimation. - Da Fan; David John Gagne II; Steven J. Greybush; Eugene E. Clothiaux; John S. Schreck; Chaopeng Shen (CoRR, 2025)