Hari S. Viswanathan

According to our database, Hari S. Viswanathan authored at least 34 papers between 2010 and 2024.

Collaborative distances:

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

2024

Bayesian learning of gas transport in three-dimensional fracture networks.

Yingqi Shi, Donald J. Berry, John Kath, Shams Lodhy, An Ly, Allon G. Percus, Jeffrey D. Hyman, Kelly Moran, Justin D. Strait, Matthew R. Sweeney, Hari S. Viswanathan, Philip Stauffer

Comput. Geosci., 2024

Information Extraction from Historical Well Records Using A Large Language Model.

Zhiwei Ma, Javier E. Santos, Greg Lackey, Hari S. Viswanathan, Daniel O'Malley

CoRR, 2024

Deep Learning-Based quantifications of methane emissions with field applications.

Ismot Jahan, Mohammed Mehana, Georgios Matheou, Hari S. Viswanathan

Int. J. Appl. Earth Obs. Geoinformation, 2024

2023

Development of the Senseiver for efficient field reconstruction from sparse observations.

Javier E. Santos, Zachary R. Fox, Arvind Mohan, Daniel O'Malley, Hari S. Viswanathan, Nicholas Lubbers

Nat. Mac. Intell., October, 2023

Learning the Factors Controlling Mineralization for Geologic Carbon Sequestration.

Aleksandra Pachalieva, Jeffrey D. Hyman, Daniel O'Malley, Hari S. Viswanathan, Gowri Srinivasan

CoRR, 2023

Reconstruction of Fields from Sparse Sensing: Differentiable Sensor Placement Enhances Generalization.

Agnese Marcato, Daniel O'Malley, Hari S. Viswanathan, Eric Guiltinan, Javier E. Santos

CoRR, 2023

Progressive reduced order modeling: empowering data-driven modeling with selective knowledge transfer.

Teeratorn Kadeethum, Daniel O'Malley, Youngsoo Choi, Hari S. Viswanathan, Hongkyu Yoon

CoRR, 2023

Impact of artificial topological changes on flow and transport through fractured media due to mesh resolution.

Aleksandra A. Pachalieva, Matthew R. Sweeney, Hari S. Viswanathan, Emily Stein, Rosie Leone, Jeffrey D. Hyman

CoRR, 2023

The FluidFlower International Benchmark Study: Process, Modeling Results, and Comparison to Experimental Data.

Bernd Flemisch, Jan M. Nordbotten, Martin A. Fernø, Ruben Juanes, Holger Class, Mojdeh Delshad, Florian Doster, Jonathan Ennis-King, Jacques Franc, Sebastian Geiger, Dennis Gläser, Christopher Green, James Gunning, Hadi Hajibeygi, Samuel J. Jackson, Mohamad Jammoul, Satish Karra, Jiawei Li, Stephan K. Matthäi, Terry Miller, Qi Shao, Catherine Spurin, Philip Stauffer, Hamdi A. Tchelepi, Xiaoming Tian, Hari S. Viswanathan, Denis V. Voskov, Yuhang Wang, Michiel Wapperom, Mary F. Wheeler, Andrew Wilkins, AbdAllah A. Youssef, Ziliang Zhang

CoRR, 2023

2022

GLUE Code: A framework handling communication and interfaces between scales.

Aleksandra Pachalieva, Robert S. Pavel, Javier E. Santos, Abdourahmane Diaw, Nicholas Lubbers, Mohammed Mehana, Jeffrey R. Haack, Hari S. Viswanathan, Daniel Livescu, Timothy C. Germann, Christoph Junghans

J. Open Source Softw., December, 2022

Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties.

Teeratorn Kadeethum, Daniel O'Malley, Youngsoo Choi, Hari S. Viswanathan, Nikolaos Bouklas, Hongkyu Yoon

Comput. Geosci., 2022

Quantum Algorithms for Geologic Fracture Networks.

Jessie M. Henderson, Marianna Podzorova, M. Cerezo, John K. Golden, Leonard Gleyzer, Hari S. Viswanathan, Daniel O'Malley

CoRR, 2022

Predictive Scale-Bridging Simulations through Active Learning.

Satish Karra, Mohammed Mehana, Nicholas Lubbers, Yu Chen, Abdourahmane Diaw, Javier E. Santos, Aleksandra Pachalieva, Robert S. Pavel, Jeffrey R. Haack, Michael M. McKerns, Christoph Junghans, Qinjun Kang, Daniel Livescu, Timothy C. Germann, Hari S. Viswanathan

CoRR, 2022

Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management.

Aleksandra Pachalieva, Daniel O'Malley, Dylan Robert Harp, Hari S. Viswanathan

CoRR, 2022

Machine Learning in Heterogeneous Porous Materials.

Marta D'Elia, Hang Deng, Cedric G. Fraces, Krishna C. Garikipati, Lori Graham-Brady, Amanda A. Howard, George Em Karniadakis, Vahid Keshavarzzadeh, Robert M. Kirby, J. Nathan Kutz, Chunhui Li, Xing Liu, Hannah Lu, Pania Newell, Daniel O'Malley, Masa Prodanovic, Gowri Srinivasan, Alexandre M. Tartakovsky, Daniel M. Tartakovsky, Hamdi A. Tchelepi, Bozo Vazic, Hari S. Viswanathan, Hongkyu Yoon, Piotr Zarzycki

CoRR, 2022

2021

A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks.

Teeratorn Kadeethum, Daniel O'Malley, Jan Niklas Fuhg, Youngsoo Choi, Jonghyun Lee, Hari S. Viswanathan, Nikolaos Bouklas

Nat. Comput. Sci., 2021

A physics-informed and hierarchically regularized data-driven model for predicting fluid flow through porous media.

Kun Wang, Yu Chen, Mohammed Mehana, Nicholas Lubbers, Kane C. Bennett, Qinjun Kang, Hari S. Viswanathan, Timothy C. Germann

J. Comput. Phys., 2021

Multi-Scale Neural Networks for to Fluid Flow in 3D Porous Media.

Javier E. Santos, Ying Yin, Honggeun Jo, Wen Pan, Qinjun Kang, Hari S. Viswanathan, Masa Prodanovic, Michael J. Pyrcz, Nicholas Lubbers

CoRR, 2021

Interrogating the performance of quantum annealing for the solution of steady-state subsurface flow.

Jessie M. Henderson, Daniel O'Malley, Hari S. Viswanathan

Proceedings of the 2021 IEEE High Performance Extreme Computing Conference, 2021

2020

A Query-Based Framework for Searching, Sorting, and Exploring Data Ensembles.

Garrett Aldrich, Jonas Lukasczyk, Jeffrey D. Hyman, Gowri Srinivasan, Hari S. Viswanathan, Christoph Garth, Heike Leitte, James P. Ahrens, Bernd Hamann

Comput. Sci. Eng., 2020

Modeling nanoconfinement effects using active learning.

Javier E. Santos, Mohammed Mehana, Hao Wu, Masa Prodanovic, Michael J. Pyrcz, Qinjun Kang, Nicholas Lubbers, Hari S. Viswanathan

CoRR, 2020

Physics-Informed Machine Learning for Real-time Reservoir Management.

Maruti Kumar Mudunuru, Daniel O'Malley, Shriram Srinivasan, Jeffrey D. Hyman, Matthew R. Sweeney, Luke Frash, Bill Carey, Michael R. Gross, Nathan J. Welch, Satish Karra, Velimir V. Vesselinov, Qinjun Kang, Hongwu Xu, Rajesh J. Pawar, Tim Carr, Liwei Li, George D. Guthrie, Hari S. Viswanathan

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

2019

PFLOTRAN-SIP: A PFLOTRAN Module for Simulating Spectral-Induced Polarization of Electrical Impedance Data.

B. Ahmmed, Maruti Kumar Mudunuru, Satish Karra, S. C. James, Hari S. Viswanathan, John A. Dunbar

CoRR, 2019

2018

Identifying Backbones in Three-Dimensional Discrete Fracture Networks: A Bipartite Graph-Based Approach.

Jeffrey D. Hyman, Aric A. Hagberg, Dave Osthus, Shriram Srinivasan, Hari S. Viswanathan, Gowri Srinivasan

Multiscale Model. Simul., 2018

Learning to fail: Predicting fracture evolution in brittle materials using recurrent graph convolutional neural networks.

Max Schwarzer, Bryce Rogan, Yadong Ruan, Zhengming Song, Diana Lee, Allon G. Percus, Viet T. Chau, Bryan A. Moore, Esteban Rougier, Hari S. Viswanathan, Gowri Srinivasan

CoRR, 2018

Estimating Failure in Brittle Materials using Graph Theory.

Maruti Kumar Mudunuru, Nishant Panda, Satish Karra, Gowri Srinivasan, Viet T. Chau, Esteban Rougier, A. Hunter, Hari S. Viswanathan

CoRR, 2018

Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications.

A. Hunter, Bryan A. Moore, Maruti Kumar Mudunuru, Viet T. Chau, Robyn L. Miller, Roselyne B. Tchoua, C. Nyshadham, Satish Karra, Dan O'Malley, Esteban Rougier, Hari S. Viswanathan, Gowri Srinivasan

CoRR, 2018

2017

Analysis and Visualization of Discrete Fracture Networks Using a Flow Topology Graph.

Garrett Aldrich, Jeffrey D. Hyman, Satish Karra, Carl W. Gable, Nataliia Makedonska, Hari S. Viswanathan, Jonathan Woodring, Bernd Hamann

IEEE Trans. Vis. Comput. Graph., 2017

Machine learning for graph-based representations of three-dimensional discrete fracture networks.

Manuel Valera, Zhengyang Guo, Priscilla Kelly, Sean Matz, Adrian Cantu, Allon G. Percus, Jeffrey D. Hyman, Gowri Srinivasan, Hari S. Viswanathan

CoRR, 2017

Learning on Graphs for Predictions of Fracture Propagation, Flow and Transport.

Hristo N. Djidjev, Daniel O'Malley, Hari S. Viswanathan, Jeffrey D. Hyman, Satish Karra, Gowri Srinivasan

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium Workshops, 2017

Image Analysis Using Convolutional Neural Networks for Modeling 2D Fracture Propagation.

Robyn L. Miller, Bryan A. Moore, Hari S. Viswanathan, Gowri Srinivasan

Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

2016

Interpolation-based reduced-order models to predict transient thermal output for enhanced geothermal systems.

Maruti Kumar Mudunuru, Satish Karra, D. R. Harp, G. D. Guthrie, Hari S. Viswanathan

CoRR, 2016

2015

dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport.

Jeffrey D. Hyman, Satish Karra, Nataliia Makedonska, Carl W. Gable, Scott L. Painter, Hari S. Viswanathan

Comput. Geosci., 2015

2010

Random walk particle tracking simulations of non-Fickian transport in heterogeneous media.

Gowri Srinivasan, Daniel M. Tartakovsky, Marco Dentz, Hari S. Viswanathan, Brian Berkowitz, B. A. Robinson

J. Comput. Phys., 2010