Isogeometric analysis of free-surface flow. - I. Akkerman; Yuri Bazilevs; Chris E. Kees; Matthew W. Farthing (J. Comput. Phys., 2011)

A conservative level set method suitable for variable-order approximations and unstructured meshes. - Chris E. Kees; I. Akkerman; Matthew W. Farthing; Yuri Bazilevs (J. Comput. Phys., 2011)

A decision making framework with MODFLOW-FMP2 via optimization: Determining trade-offs in crop selection. - Kathleen R. Fowler; Eleanor W. Jenkins; C. Ostrove; J. C. Chrispell; Matthew W. Farthing; Matthew D. Parno (Environ. Model. Softw., 2015)

POD-based model reduction for stabilized finite element approximations of shallow water flows. - Alexander Lozovskiy; Matthew W. Farthing; Chris E. Kees; Eduardo Gildin (J. Comput. Appl. Math., 2016)

Formulation and application of the adaptive hydraulics three-dimensional shallow water and transport models. - Corey Jason Trahan; Gaurav Savant; R. C. Berger; Matthew W. Farthing; T. O. McAlpin; L. Pettey; G. K. Choudhary; Clint N. Dawson (J. Comput. Phys., 2018)

Well-Balanced Second-Order Finite Element Approximation of the Shallow Water Equations with Friction. - Jean-Luc Guermond; Manuel Quezada de Luna; Bojan Popov; Christopher E. Kees; Matthew W. Farthing (SIAM J. Sci. Comput., 2018)

A 2D Fully Convolutional Neural Network for Nearshore And Surf-Zone Bathymetry Inversion from Synthetic Imagery of Surf-Zone using the Model Celeris. - Adam Collins; Katherine L. Brodie; Andrew Spicer Bak; Tyler J. Hesser; Matthew W. Farthing; Douglas W. Gamble; Joseph W. Long (AAAI Spring Symposium: MLPS, 2020)

Preface. - Jonghyun Lee 005; Eric F. Darve; Peter K. Kitanidis; Matthew W. Farthing; Tyler J. Hesser (AAAI Spring Symposium: MLPS, 2020)

Surfzone Topography-informed Deep Learning Techniques to Nearshore Bathymetry with Sparse Measurements. - Yizhou Qian; Hojat Ghorbanidehno; Matthew W. Farthing; Ty Hesser; Peter K. Kitanidis; Eric F. Darve (AAAI Spring Symposium: MLPS, 2020)

Application of Deep Learning-based Interpolation Methods to Nearshore Bathymetry. - Yizhou Qian; Mojtaba Forghani; Jonghyun Lee 005; Matthew W. Farthing; Tyler J. Hesser; Peter K. Kitanidis; Eric Darve (CoRR, 2020)

Application of deep learning to large scale riverine flow velocity estimation. - Mojtaba Forghani; Yizhou Qian; Jonghyun Lee 005; Matthew W. Farthing; Tyler J. Hesser; Peter K. Kitanidis; Eric F. Darve (CoRR, 2020)

Bathymetric Inversion and Uncertainty Estimation from Synthetic Surf-Zone Imagery with Machine Learning. - Adam Collins; Katherine L. Brodie; Andrew Spicer Bak; Tyler J. Hesser; Matthew W. Farthing; Jonghyun Lee 005; Joseph W. Long (Remote. Sens., 2020)

Neural Ordinary Differential Equations for Data-Driven Reduced Order Modeling of Environmental Hydrodynamics. - Sourav Dutta; Peter Rivera-Casillas; Matthew W. Farthing (AAAI Spring Symposium: MLPS, 2021)

Deep Learning-based Fast Solver of the Shallow Water Equations. - Mojtaba Forghani; Yizhou Qian; Jonghyun Lee 005; Matthew W. Farthing; Tyler J. Hesser; Peter K. Kitanidis; Eric Darve (AAAI Spring Symposium: MLPS, 2021)

Data-driven reduced order modeling of environmental hydrodynamics using deep autoencoders and neural ODEs. - Sourav Dutta; Peter Rivera-Casillas; Orie M. Cecil; Matthew W. Farthing; Emma Perracchione; Mario Putti (CoRR, 2021)

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry. - Mojtaba Forghani; Yizhou Qian; Jonghyun Lee 005; Matthew W. Farthing; Tyler J. Hesser; Peter K. Kitanidis; Eric F. Darve (CoRR, 2021)

Intrinsic finite element method for advection-diffusion-reaction equations on surfaces. - Elena Bachini; Matthew W. Farthing; Mario Putti (J. Comput. Phys., 2021)

A greedy non-intrusive reduced order model for shallow water equations. - Sourav Dutta; Matthew W. Farthing; Emma Perracchione; Gaurav Savant; Mario Putti (J. Comput. Phys., 2021)

Development of a Fully Convolutional Neural Network to Derive Surf-Zone Bathymetry from Close-Range Imagery of Waves in Duck, NC. - Adam Collins; Matthew P. Geheran; Tyler J. Hesser; Andrew Spicer Bak; Katherine L. Brodie; Matthew W. Farthing (Remote. Sens., 2021)

pyNIROM - A suite of python modules for non-intrusive reduced order modeling of time-dependent problems. - Sourav Dutta; Peter Rivera-Casillas; Orie M. Cecil; Matthew W. Farthing (Softw. Impacts, 2021)

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)

Automated Extraction of a Depth-Defined Wave Runup Time Series From Lidar Data Using Deep Learning. - Adam Collins; Annika O'Dea; Katherine L. Brodie; Andrew Spicer Bak; Tyler J. Hesser; Nicholas J. Spore; Matthew W. Farthing (IEEE Trans. Geosci. Remote. Sens., 2023)

Multi-fidelity Hamiltonian Monte Carlo. - Dhruv V. Patel; Jonghyun Lee 005; Matthew W. Farthing; Peter K. Kitanidis; Eric F. Darve (CoRR, 2024)

A Neural Operator-Based Emulator for Regional Shallow Water Dynamics. - Peter Rivera-Casillas; Sourav Dutta; Shukai Cai; Mark Loveland; Kamaljyoti Nath; Khemraj Shukla; Corey Jason Trahan; Jonghyun Lee 005; Matthew W. Farthing; Clint Dawson 001 (CoRR, 2025)