124 citations · 212 across the 18 of their papers we have counts for
20 papers
Model-agnostic stochastic model predictive control
Tapas Tripura, Souvik Chakraborty
We propose a model-agnostic stochastic predictive control (MASMPC) algorithm for dynamical systems. The proposed approach first discovers \textit{interpretable} governing different…
Uncertainty Quantification and Sensitivity analysis for Digital Twin Enabling Technology: Application for BISON Fuel Performance Code
Kazuma Kobayashi, Dinesh Kumar, Matthew Bonney +3
To understand the potential of intelligent confirmatory tools, the U.S. Nuclear Regulatory Committee (NRC) initiated a future-focused research project to assess the regulatory viab…
Stochastic projection based approach for gradient free physics informed learning
Navaneeth N, Souvik Chakraborty
We propose a stochastic projection-based gradient free physics-informed neural network. The proposed approach, referred to as the stochastic projection based physics informed neura…
Wavelet neural operator: a neural operator for parametric partial differential equations
Tapas Tripura, Souvik Chakraborty
With massive advancements in sensor technologies and Internet-of-things, we now have access to terabytes of historical data; however, there is a lack of clarity in how to best expl…
Energy networks for state estimation with random sensors using sparse labels
Yash Kumar, Souvik Chakraborty
State estimation is required whenever we deal with high-dimensional dynamical systems, as the complete measurement is often unavailable. It is key to gaining insight, performing co…
Assessment of DeepONet for reliability analysis of stochastic nonlinear dynamical systems
Shailesh Garg, Harshit Gupta, Souvik Chakraborty
Time dependent reliability analysis and uncertainty quantification of structural system subjected to stochastic forcing function is a challenging endeavour as it necessitates consi…