242 citations · 629 across the 42 of their papers we have counts for
9 papers · 1 filter
Gated Linear Model induced U-net for surrogate modeling and uncertainty quantification
Sai Krishna Mendu, Souvik Chakraborty
We propose a novel deep learning based surrogate model for solving high-dimensional uncertainty quantification and uncertainty propagation problems. The proposed deep learning arch…
A deep learning based surrogate model for stochastic simulators
Akshay Thakur, Souvik Chakraborty
We propose a deep learning-based surrogate model for stochastic simulators. The basic idea is to use generative neural network to approximate the stochastic response. The challenge…
Physics-integrated hybrid framework for model form error identification in nonlinear dynamical systems
Shailesh Garg, Souvik Chakraborty, Budhaditya Hazra
For real-life nonlinear systems, the exact form of nonlinearity is often not known and the known governing equations are often based on certain assumptions and approximations. Such…
Generalized weakly corrected Milstein solutions to stochastic differential equations
Tapas Tripura, Budhaditya Hazra, Souvik Chakraborty
In this work, weakly corrected explicit, semi-implicit and implicit Milstein approximations are presented for the solution of nonlinear stochastic differential equations. The solut…
A change of measure enhanced near exact Euler Maruyama scheme for the solution to nonlinear stochastic dynamical systems
Tapas Tripura, Mohammad Imran, Budhaditya Hazra +1
The present study utilizes the Girsanov transformation based framework for solving a nonlinear stochastic dynamical system in an efficient way in comparison to other available appr…
GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations
Yash Kumar, Souvik Chakraborty
The physical world is governed by the laws of physics, often represented in form of nonlinear partial differential equations (PDEs). Unfortunately, solution of PDEs is non-trivial…
Surrogate assisted active subspace and active subspace assisted surrogate -- A new paradigm for high dimensional structural reliability analysis
Navaneeth N., Souvik Chakraborty
Performing reliability analysis on complex systems is often computationally expensive. In particular, when dealing with systems having high input dimensionality, reliability estima…
Machine learning based digital twin for stochastic nonlinear multi-degree of freedom dynamical system
Shailesh Garg, Ankush Gogoi, Souvik Chakraborty +1
The potential of digital twin technology is immense, specifically in the infrastructure, aerospace, and automotive sector. However, practical implementation of this technology is n…
State estimation with limited sensors -- A deep learning based approach
Yash Kumar, Pranav Bahl, Souvik Chakraborty
The importance of state estimation in fluid mechanics is well-established; it is required for accomplishing several tasks including design/optimization, active control, and future…