Matthew W. Farthing
Orcid: 0000-0002-7301-6359Affiliations:
- U.S. Army Corps of Engineers, Coastal and Hydraulics Laboratory, Vicksburg, MS, USA
According to our database1,
Matthew W. Farthing
authored at least 23 papers
between 2011 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2024
2023
Automated Extraction of a Depth-Defined Wave Runup Time Series From Lidar Data Using Deep Learning.
IEEE Trans. Geosci. Remote. Sens., 2023
Differentiable modeling to unify machine learning and physical models and advance Geosciences.
CoRR, 2023
2021
pyNIROM - A suite of python modules for non-intrusive reduced order modeling of time-dependent problems.
Softw. Impacts, 2021
Development of a Fully Convolutional Neural Network to Derive Surf-Zone Bathymetry from Close-Range Imagery of Waves in Duck, NC.
Remote. Sens., 2021
J. Comput. Phys., 2021
Intrinsic finite element method for advection-diffusion-reaction equations on surfaces.
J. Comput. Phys., 2021
Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry.
CoRR, 2021
Data-driven reduced order modeling of environmental hydrodynamics using deep autoencoders and neural ODEs.
CoRR, 2021
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.
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.
Remote. Sens., 2020
CoRR, 2020
CoRR, 2020
Surfzone Topography-informed Deep Learning Techniques to Nearshore Bathymetry with Sparse Measurements.
Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to, 2020
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.
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.
SIAM J. Sci. Comput., 2018
Formulation and application of the adaptive hydraulics three-dimensional shallow water and transport models.
J. Comput. Phys., 2018
2016
POD-based model reduction for stabilized finite element approximations of shallow water flows.
J. Comput. Appl. Math., 2016
2015
A decision making framework with MODFLOW-FMP2 via optimization: Determining trade-offs in crop selection.
Environ. Model. Softw., 2015
2011
A conservative level set method suitable for variable-order approximations and unstructured meshes.
J. Comput. Phys., 2011