164 citations · 172 across the 5 of their papers we have counts for
6 papers
Active Learning Discovery of High Temperature Oxidation Resistant Refractory Complex Concentrated Alloys
Akhil Bejjipurapu, Sharmila Karumuri, Joseph C. Flanagan +5
Refractory complex concentrated alloys (RCCAs) are of significant interest for advanced high-temperature applications, owing to their broad compositional range and potential for at…
Physics-Informed Latent Neural Operator for Real-time Predictions of time-dependent parametric PDEs
Sharmila Karumuri, Lori Graham-Brady, Somdatta Goswami
Deep operator network (DeepONet) has shown significant promise as surrogate models for systems governed by partial differential equations (PDEs), enabling accurate mappings between…
Efficient Training of Deep Neural Operator Networks via Randomized Sampling
Sharmila Karumuri, Lori Graham-Brady, Somdatta Goswami
Neural operators (NOs) employ deep neural networks to learn mappings between infinite-dimensional function spaces. Deep operator network (DeepONet), a popular NO architecture, has…
Mass uptake during oxidation of metallic alloys: literature data collection, analysis, and FAIR sharing
Saswat Mishra, Sharmila Karumuri, Vincent Mika +6
The area-normalized change of mass (m/A) with time during the oxidation of metallic alloys is commonly used to assess oxidation resistance. Analyses of such data can also aid in…
Learning to solve Bayesian inverse problems: An amortized variational inference approach using Gaussian and Flow guides
Sharmila Karumuri, Ilias Bilionis
Inverse problems, i.e., estimating parameters of physical models from experimental data, are ubiquitous in science and engineering. The Bayesian formulation is the gold standard be…
Simulator-free Solution of High-Dimensional Stochastic Elliptic Partial Differential Equations using Deep Neural Networks
Sharmila Karumuri, Rohit Tripathy, Ilias Bilionis +1
Stochastic partial differential equations (SPDEs) are ubiquitous in engineering and computational sciences. The stochasticity arises as a consequence of uncertainty in input parame…