Matthew W. Farthing

According to our database, Matthew W. Farthing authored at least 22 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

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, Yi Zheng, Ciaran J. Harman, Martyn Clark, Matthew W. Farthing, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Tirthankar Roy, Chonggang Xu, Kathryn Lawson

CoRR, 2023

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

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

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

Intrinsic finite element method for advection-diffusion-reaction equations on surfaces.

Elena Bachini, Matthew W. Farthing, Mario Putti

J. Comput. Phys., 2021

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry.

Mojtaba Forghani, Yizhou Qian, Jonghyun Lee, Matthew W. Farthing, Tyler J. Hesser, Peter K. Kitanidis, Eric F. Darve

CoRR, 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

Preface.

Jonghyun Lee, Eric F. Darve, Peter K. Kitanidis, Matthew W. Farthing, Tyler J. Hesser

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

Deep Learning-based Fast Solver of the Shallow Water Equations.

Mojtaba Forghani, Yizhou Qian, Jonghyun Lee, Matthew W. Farthing, Tyler J. Hesser, Peter K. Kitanidis, Eric Darve

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

Neural Ordinary Differential Equations for Data-Driven Reduced Order Modeling of Environmental Hydrodynamics.

Sourav Dutta, Peter Rivera-Casillas, Matthew W. Farthing

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

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, Joseph W. Long

Remote. Sens., 2020

Application of deep learning to large scale riverine flow velocity estimation.

Mojtaba Forghani, Yizhou Qian, Jonghyun Lee, Matthew W. Farthing, Tyler J. Hesser, Peter K. Kitanidis, Eric F. Darve

CoRR, 2020

Application of Deep Learning-based Interpolation Methods to Nearshore Bathymetry.

Yizhou Qian, Mojtaba Forghani, Jonghyun Harry Lee, Matthew W. Farthing, Tyler J. Hesser, Peter K. Kitanidis, Eric Darve

CoRR, 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

Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to, 2020

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

Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to, 2020

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

Formulation and application of the adaptive hydraulics three-dimensional shallow water and transport models.

C. J. Trahan, Gaurav Savant, R. C. Berger, Matthew W. Farthing, T. O. McAlpin, L. Pettey, G. K. Choudhary, Clint N. Dawson

J. Comput. Phys., 2018

2016

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

2015

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

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

Isogeometric analysis of free-surface flow.

I. Akkerman, Yuri Bazilevs, Chris E. Kees, Matthew W. Farthing

J. Comput. Phys., 2011