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)

Predicting Dynamic Trends of the Atlantic Meridional Overturning Circulation for Transient and Stochastic Forcing Effects. - A. Pampell; A. B. Aceves; Gowri Srinivasan (SIAM/ASA J. Uncertain. Quantification, 2014)

Efficient and robust classification of seismic data using nonlinear support vector machines. - Kyle S. Hickmann; Jeffrey D. Hyman; Gowri Srinivasan (ACSSC, 2017)

Image Analysis Using Convolutional Neural Networks for Modeling 2D Fracture Propagation. - Robyn L. Miller; Bryan A. Moore; Hari S. Viswanathan; Gowri Srinivasan (ICDM Workshops, 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 (IPDPS Workshops, 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)

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)

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)

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)

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)

Multilevel Graph Partitioning for Three-Dimensional Discrete Fracture Network Flow Simulations. - Hayato Ushijima-Mwesigwa; Jeffrey D. Hyman; Aric A. Hagberg; Ilya Safro; Satish Karra; Carl W. Gable; Gowri Srinivasan (CoRR, 2019)

Physics-Informed Spatiotemporal Deep Learning for Emulating Coupled Dynamical Systems. - Anishi Mehta; Cory Braker Scott; Diane Oyen; Nishant Panda; Gowri Srinivasan (AAAI Spring Symposium: MLPS, 2020)

Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments Using Machine Learning. - Julia B. Nakhleh; M. Giselle Fernández-Godino; Michael J. Grosskopf; Brandon M. Wilson; John Kline; Gowri Srinivasan (CoRR, 2020)

Identifying Entangled Physics Relationships through Sparse Matrix Decomposition to Inform Plasma Fusion Design. - M. Giselle Fernández-Godino; Michael J. Grosskopf; Julia B. Nakhleh; Brandon M. Wilson; John Kline; Gowri Srinivasan (CoRR, 2020)

StressNet: Deep Learning to Predict Stress With Fracture Propagation in Brittle Materials. - Yinan Wang; Diane Oyen; Weihong Guo 001; Anishi Mehta; Cory Braker Scott; Nishant Panda; M. Giselle Fernández-Godino; Gowri Srinivasan; Xiaowei Yue (CoRR, 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)

Mesoscale informed parameter estimation through machine learning: A case-study in fracture modeling. - Nishant Panda; Dave Osthus; Gowri Srinivasan; Daniel O'Malley; Viet T. Chau; Diane Oyen; Humberto Godinez (J. Comput. Phys., 2020)

A Probabilistic Clustering Approach for Identifying Primary Subnetworks of Discrete Fracture Networks with Quantified Uncertainty. - Dave Osthus; Jeffrey D. Hyman; Satish Karra; Nishant Panda; Gowri Srinivasan (SIAM/ASA J. Uncertain. Quantification, 2020)

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; et al. (CoRR, 2022)

Learning the Factors Controlling Mineralization for Geologic Carbon Sequestration. - Aleksandra Pachalieva; Jeffrey D. Hyman; Daniel O'Malley; Hari S. Viswanathan; Gowri Srinivasan (CoRR, 2023)