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Souvik Chakraborty

Orcid: 0000-0003-2383-2603

According to our database1, Souvik Chakraborty authored at least 53 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Discovering interpretable Lagrangian of dynamical systems from data.
[BibTeX]
[DOI]
Tapas Tripura
,
Souvik Chakraborty
Comput. Phys. Commun., January, 2024

PhyPlan: Compositional and Adaptive Physical Task Reasoning with Physics-Informed Skill Networks for Robot Manipulators.
[BibTeX]
[DOI]
Harshil Vagadia
,
Mudit Chopra
,
Abhinav Barnawal
,
Tamajit Banerjee
,
Shreshth Tuli
,
Souvik Chakraborty
,
Rohan Paul
CoRR, 2024

Generative adversarial wavelet neural operator: Application to fault detection and isolation of multivariate time series data.
[BibTeX]
[DOI]
Jyoti Rani
,
Tapas Tripura
,
Hariprasad Kodamana
,
Souvik Chakraborty
CoRR, 2024

2023
Efficient hybrid topology optimization using GPU and homogenization-based multigrid approach.
[BibTeX]
[DOI]
Arya Prakash Padhi
,
Souvik Chakraborty
,
Anupam Chakrabarti
,
Rajib Chowdhury
Eng. Comput., October, 2023

MAntRA: A framework for model agnostic reliability analysis.
[BibTeX]
[DOI]
Yogesh Chandrakant Mathpati
,
Kalpesh Sanjay More
,
Tapas Tripura
,
Rajdip Nayek
,
Souvik Chakraborty
Reliab. Eng. Syst. Saf., July, 2023

Deep Physics Corrector: A physics enhanced deep learning architecture for solving stochastic differential equations.
[BibTeX]
[DOI]
Tushar
,
Souvik Chakraborty
J. Comput. Phys., April, 2023

A wavelet neural operator based elastography for localization and quantification of tumors.
[BibTeX]
[DOI]
Tapas Tripura
,
Abhilash Awasthi
,
Sitikantha Roy
,
Souvik Chakraborty
Comput. Methods Programs Biomed., April, 2023

VB-DeepONet: A Bayesian operator learning framework for uncertainty quantification.
[BibTeX]
[DOI]
Shailesh Garg
,
Souvik Chakraborty
Eng. Appl. Artif. Intell., 2023

Neuroscience inspired scientific machine learning (Part-2): Variable spiking wavelet neural operator.
[BibTeX]
[DOI]
Shailesh Garg
,
Souvik Chakraborty
CoRR, 2023

Neuroscience inspired scientific machine learning (Part-1): Variable spiking neuron for regression.
[BibTeX]
[DOI]
Shailesh Garg
,
Souvik Chakraborty
CoRR, 2023

A foundational neural operator that continuously learns without forgetting.
[BibTeX]
[DOI]
Tapas Tripura
,
Souvik Chakraborty
CoRR, 2023

A Bayesian framework for discovering interpretable Lagrangian of dynamical systems from data.
[BibTeX]
[DOI]
Tapas Tripura
,
Souvik Chakraborty
CoRR, 2023

Waveformer for modelling dynamical systems.
[BibTeX]
[DOI]
Navaneeth N.
,
Souvik Chakraborty
CoRR, 2023

DPA-WNO: A gray box model for a class of stochastic mechanics problem.
[BibTeX]
[DOI]
Tushar
,
Souvik Chakraborty
CoRR, 2023

Discovering stochastic partial differential equations from limited data using variational Bayes inference.
[BibTeX]
[DOI]
Yogesh Chandrakant Mathpati
,
Tapas Tripura
,
Rajdip Nayek
,
Souvik Chakraborty
CoRR, 2023

A Bayesian Framework for learning governing Partial Differential Equation from Data.
[BibTeX]
[DOI]
Kalpesh Sanjay More
,
Tapas Tripura
,
Rajdip Nayek
,
Souvik Chakraborty
CoRR, 2023

Physics informed WNO.
[BibTeX]
[DOI]
Navaneeth N.
,
Tapas Tripura
,
Souvik Chakraborty
CoRR, 2023

Randomized prior wavelet neural operator for uncertainty quantification.
[BibTeX]
[DOI]
Shailesh Garg
,
Souvik Chakraborty
CoRR, 2023

Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life.
[BibTeX]
[DOI]
Kazuma Kobayashi
,
Bader Almutairi
,
Md. Nazmus Sakib
,
Souvik Chakraborty
,
Syed B. Alam
CoRR, 2023

2022
State estimation with limited sensors - A deep learning based approach.
[BibTeX]
[DOI]
Yash Kumar
,
Pranav Bahl
,
Souvik Chakraborty
J. Comput. Phys., 2022

Probabilistic machine learning based predictive and interpretable digital twin for dynamical systems.
[BibTeX]
[DOI]
Tapas Tripura
,
Aarya Sheetal Desai
,
Sondipon Adhikari
,
Souvik Chakraborty
CoRR, 2022

Physics-Informed Multi-Stage Deep Learning Framework Development for Digital Twin-Centred State-Based Reactor Power Prediction.
[BibTeX]
[DOI]
James Daniell
,
Kazuma Kobayashi
,
Susmita Naskar
,
Dinesh Kumar
,
Souvik Chakraborty
,
Ayodeji Alajo
,
Ethan Taber
,
Joseph Graham
,
Syed B. Alam
CoRR, 2022

Model-agnostic stochastic model predictive control.
[BibTeX]
[DOI]
Tapas Tripura
,
Souvik Chakraborty
CoRR, 2022

Stochastic projection based approach for gradient free physics informed learning.
[BibTeX]
[DOI]
Navaneeth N.
,
Souvik Chakraborty
CoRR, 2022

Multi-fidelity wavelet neural operator with application to uncertainty quantification.
[BibTeX]
[DOI]
Akshay Thakur
,
Tapas Tripura
,
Souvik Chakraborty
CoRR, 2022

Variational Bayes Deep Operator Network: A data-driven Bayesian solver for parametric differential equations.
[BibTeX]
[DOI]
Shailesh Garg
,
Souvik Chakraborty
CoRR, 2022

Wavelet neural operator: a neural operator for parametric partial differential equations.
[BibTeX]
[DOI]
Tapas Tripura
,
Souvik Chakraborty
CoRR, 2022

Energy networks for state estimation with random sensors using sparse labels.
[BibTeX]
[DOI]
Yash Kumar
,
Souvik Chakraborty
CoRR, 2022

Koopman operator for time-dependent reliability analysis.
[BibTeX]
[DOI]
Navaneeth N.
,
Souvik Chakraborty
CoRR, 2022

Assessment of DeepONet for reliability analysis of stochastic nonlinear dynamical systems.
[BibTeX]
[DOI]
Shailesh Garg
,
Harshit Gupta
,
Souvik Chakraborty
CoRR, 2022

Deep Capsule Encoder-Decoder Network for Surrogate Modeling and Uncertainty Quantification.
[BibTeX]
[DOI]
Akshay Thakur
,
Souvik Chakraborty
CoRR, 2022

2021
Transfer learning based multi-fidelity physics informed deep neural network.
[BibTeX]
[DOI]
Souvik Chakraborty
J. Comput. Phys., 2021

Gated Linear Model induced U-net for surrogate modeling and uncertainty quantification.
[BibTeX]
[DOI]
Sai Krishna Mendu
,
Souvik Chakraborty
CoRR, 2021

A deep learning based surrogate model for stochastic simulators.
[BibTeX]
[DOI]
Akshay Thakur
,
Souvik Chakraborty
CoRR, 2021

Physics-integrated hybrid framework for model form error identification in nonlinear dynamical systems.
[BibTeX]
[DOI]
Shailesh Garg
,
Souvik Chakraborty
,
Budhaditya Hazra
CoRR, 2021

Generalized weakly corrected Milstein solutions to stochastic differential equations.
[BibTeX]
[DOI]
Tapas Tripura
,
Budhaditya Hazra
,
Souvik Chakraborty
CoRR, 2021

A change of measure enhanced near exact Euler Maruyama scheme for the solution to nonlinear stochastic dynamical systems.
[BibTeX]
[DOI]
Tapas Tripura
,
Mohammad Imran
,
Budhaditya Hazra
,
Souvik Chakraborty
CoRR, 2021

GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations.
[BibTeX]
[DOI]
Yash Kumar
,
Souvik Chakraborty
CoRR, 2021

Surrogate assisted active subspace and active subspace assisted surrogate - A new paradigm for high dimensional structural reliability analysis.
[BibTeX]
[DOI]
Navaneeth N.
,
Souvik Chakraborty
CoRR, 2021

Machine learning based digital twin for stochastic nonlinear multi-degree of freedom dynamical system.
[BibTeX]
[DOI]
Shailesh Garg
,
Ankush Gogoi
,
Souvik Chakraborty
,
Budhaditya Hazra
CoRR, 2021

2020
Machine learning based digital twin for dynamical systems with multiple time-scales.
[BibTeX]
[DOI]
Souvik Chakraborty
,
Sondipon Adhikari
CoRR, 2020

The role of surrogate models in the development of digital twins of dynamic systems.
[BibTeX]
[DOI]
Souvik Chakraborty
,
Sondipon Adhikari
,
Ranjan Ganguli
CoRR, 2020

2019
Transfer learning enhanced physics informed neural network for phase-field modeling of fracture.
[BibTeX]
[DOI]
Somdatta Goswami
,
Cosmin Anitescu
,
Souvik Chakraborty
,
Timon Rabczuk
CoRR, 2019

Threshold shift method for reliability-based design optimization.
[BibTeX]
[DOI]
Somdatta Goswami
,
Souvik Chakraborty
,
Rajib Chowdhury
,
Timon Rabczuk
CoRR, 2019

A Gaussian process latent force model for joint input-state estimation in linear structural systems.
[BibTeX]
[DOI]
Rajdip Nayek
,
Souvik Chakraborty
,
Sriram Narasimhan
CoRR, 2019

2018
Dynamical accelerated performance measure approach for efficient reliability-based design optimization with highly nonlinear probabilistic constraints.
[BibTeX]
[DOI]
Behrooz Keshtegar
,
Souvik Chakraborty
Reliab. Eng. Syst. Saf., 2018

Hybrid Reliability Analysis Framework for Reliability Analysis of Tunnels.
[BibTeX]
[DOI]
Souvik Chakraborty
,
Dipaloke Majumder
J. Comput. Civ. Eng., 2018

Efficient data-driven reduced-order models for high-dimensional multiscale dynamical systems.
[BibTeX]
[DOI]
Souvik Chakraborty
,
Nicholas Zabaras
Comput. Phys. Commun., 2018

2017
A hybrid approach for global sensitivity analysis.
[BibTeX]
[DOI]
Souvik Chakraborty
,
Rajib Chowdhury
Reliab. Eng. Syst. Saf., 2017

An efficient algorithm for building locally refined hp - adaptive H-PCFE: Application to uncertainty quantification.
[BibTeX]
[DOI]
Souvik Chakraborty
,
Rajib Chowdhury
J. Comput. Phys., 2017

Moment Independent Sensitivity Analysis: H-PCFE-Based Approach.
[BibTeX]
[DOI]
Souvik Chakraborty
,
Rajib Chowdhury
J. Comput. Civ. Eng., 2017

2016
Sequential experimental design based generalised ANOVA.
[BibTeX]
[DOI]
Souvik Chakraborty
,
Rajib Chowdhury
J. Comput. Phys., 2016

Modelling uncertainty in incompressible flow simulation using Galerkin based generalized ANOVA.
[BibTeX]
[DOI]
Souvik Chakraborty
,
Rajib Chowdhury
Comput. Phys. Commun., 2016


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