Souvik Chakraborty

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 68

Top Topics

Dynamical Systems

Reliability Analysis

Differential Equations

Top Venues

J. Comput. Phys.

Comput. Phys. Commun.

Reliab. Eng. Syst. Saf.

Publications

Hartej Soin, Tapas Tripura, Souvik Chakraborty
Generative flow induced neural architecture search: Towards discovering optimal architecture in wavelet neural operator. CoRR (2024)
Harshil Vagadia, Mudit Chopra, Abhinav Barnawal, Tamajit Banerjee, Shreshth Tuli, Souvik Chakraborty, Rohan Paul
PhyPlan: Compositional and Adaptive Physical Task Reasoning with Physics-Informed Skill Networks for Robot Manipulators. CoRR (2024)
Sawan Kumar, Rajdip Nayek, Souvik Chakraborty
Neural Operator induced Gaussian Process framework for probabilistic solution of parametric partial differential equations. CoRR (2024)
Shailesh Garg, Souvik Chakraborty
Neuroscience inspired neural operator for partial differential equations. J. Comput. Phys. 515 (2024)
Tapas Tripura, Souvik Chakraborty
Discovering interpretable Lagrangian of dynamical systems from data. Comput. Phys. Commun. 294 (2024)
Arya Prakash Padhi, Souvik Chakraborty, Anupam Chakrabarti, Rajib Chowdhury
Deep learning accelerated efficient framework for topology optimization. Eng. Appl. Artif. Intell. 133 (2024)
Jagajyoti Panda, Mudit Chopra, Vasant Matsagar, Souvik Chakraborty
Continuous control of structural vibrations using hybrid deep reinforcement learning policy. Expert Syst. Appl. 252 (2024)
Calvin Alvares, Souvik Chakraborty
Discovering governing equation in structural dynamics from acceleration-only measurements. CoRR (2024)
Mudit Chopra, Abhinav Barnawal, Harshil Vagadia, Tamajit Banerjee, Shreshth Tuli, Souvik Chakraborty, Rohan Paul
PhyPlan: Generalizable and Rapid Physical Task Planning with Physics Informed Skill Networks for Robot Manipulators. CoRR (2024)
Akshay Thakur, Souvik Chakraborty
MD-NOMAD: Mixture density nonlinear manifold decoder for emulating stochastic differential equations and uncertainty propagation. CoRR (2024)
Jyoti Rani, Tapas Tripura, Hariprasad Kodamana, Souvik Chakraborty
Generative adversarial wavelet neural operator: Application to fault detection and isolation of multivariate time series data. CoRR (2024)
Yogesh Chandrakant Mathpati, Kalpesh Sanjay More, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
MAntRA: A framework for model agnostic reliability analysis. Reliab. Eng. Syst. Saf. 235 (2023)
Navaneeth N., Tapas Tripura, Souvik Chakraborty
Physics informed WNO. CoRR (2023)
Shailesh Garg, Souvik Chakraborty
Neuroscience inspired scientific machine learning (Part-2): Variable spiking wavelet neural operator. CoRR (2023)
Tapas Tripura, Souvik Chakraborty
A foundational neural operator that continuously learns without forgetting. CoRR (2023)
Yogesh Chandrakant Mathpati, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
Discovering stochastic partial differential equations from limited data using variational Bayes inference. CoRR (2023)
Shailesh Garg, Souvik Chakraborty
Neuroscience inspired scientific machine learning (Part-1): Variable spiking neuron for regression. CoRR (2023)
Tushar, Souvik Chakraborty
DPA-WNO: A gray box model for a class of stochastic mechanics problem. CoRR (2023)
Kazuma Kobayashi, Bader Almutairi, Md. Nazmus Sakib, Souvik Chakraborty, Syed B. Alam
Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life. CoRR (2023)
Kalpesh Sanjay More, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
A Bayesian Framework for learning governing Partial Differential Equation from Data. CoRR (2023)
Tapas Tripura, Souvik Chakraborty
A Bayesian framework for discovering interpretable Lagrangian of dynamical systems from data. CoRR (2023)
Arya Prakash Padhi, Souvik Chakraborty, Anupam Chakrabarti, Rajib Chowdhury
Efficient hybrid topology optimization using GPU and homogenization-based multigrid approach. Eng. Comput. 39 (5) (2023)
Tapas Tripura, Abhilash Awasthi, Sitikantha Roy, Souvik Chakraborty
A wavelet neural operator based elastography for localization and quantification of tumors. Comput. Methods Programs Biomed. 232 (2023)
Navaneeth N., Souvik Chakraborty
Waveformer for modelling dynamical systems. CoRR (2023)
Shailesh Garg, Souvik Chakraborty
VB-DeepONet: A Bayesian operator learning framework for uncertainty quantification. Eng. Appl. Artif. Intell. 118 (2023)
Tapas Tripura, Souvik Chakraborty
Discovering interpretable Lagrangian of dynamical systems from data. CoRR (2023)
Shailesh Garg, Souvik Chakraborty
Randomized prior wavelet neural operator for uncertainty quantification. CoRR (2023)
Tushar, Souvik Chakraborty
Deep Physics Corrector: A physics enhanced deep learning architecture for solving stochastic differential equations. J. Comput. Phys. 479 (2023)
Tapas Tripura, Aarya Sheetal Desai, Sondipon Adhikari, Souvik Chakraborty
Probabilistic machine learning based predictive and interpretable digital twin for dynamical systems. CoRR (2022)
Arya Prakash Padhi, Souvik Chakraborty, Anupam Chakrabarti, Rajib Chowdhury
Efficient hybrid topology optimization using GPU and homogenization based multigrid approach. CoRR (2022)
Navaneeth N., Souvik Chakraborty
Stochastic projection based approach for gradient free physics informed learning. CoRR (2022)
Akshay Thakur, Tapas Tripura, Souvik Chakraborty
Multi-fidelity wavelet neural operator with application to uncertainty quantification. CoRR (2022)
Yash Kumar, Pranav Bahl, Souvik Chakraborty
State estimation with limited sensors - A deep learning based approach. J. Comput. Phys. 457 (2022)
Navaneeth N., Souvik Chakraborty
Koopman operator for time-dependent reliability analysis. CoRR (2022)
James Daniell, Kazuma Kobayashi, Susmita Naskar, Dinesh Kumar, Souvik Chakraborty, Ayodeji Alajo, Ethan Taber, Joseph Graham, Syed B. Alam
Physics-Informed Multi-Stage Deep Learning Framework Development for Digital Twin-Centred State-Based Reactor Power Prediction. CoRR (2022)
Shailesh Garg, Souvik Chakraborty
Variational Bayes Deep Operator Network: A data-driven Bayesian solver for parametric differential equations. CoRR (2022)
Tushar, Souvik Chakraborty
Deep Physics Corrector: A physics enhanced deep learning architecture for solving stochastic differential equations. CoRR (2022)
Tapas Tripura, Souvik Chakraborty
Model-agnostic stochastic model predictive control. CoRR (2022)
Tapas Tripura, Souvik Chakraborty
Wavelet neural operator: a neural operator for parametric partial differential equations. CoRR (2022)
Yogesh Chandrakant Mathpati, Kalpesh Sanjay More, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
MAntRA: A framework for model agnostic reliability analysis. CoRR (2022)
Yash Kumar, Souvik Chakraborty
Energy networks for state estimation with random sensors using sparse labels. CoRR (2022)
Siladittya Manna, Souvik Chakraborty
BYOLMed3D: Self-Supervised Representation Learning of Medical Videos using Gradient Accumulation Assisted 3D BYOL Framework. CoRR (2022)
Akshay Thakur, Souvik Chakraborty
Deep Capsule Encoder-Decoder Network for Surrogate Modeling and Uncertainty Quantification. CoRR (2022)
Shailesh Garg, Harshit Gupta, Souvik Chakraborty
Assessment of DeepONet for reliability analysis of stochastic nonlinear dynamical systems. CoRR (2022)
Tapas Tripura, Mohammad Imran, Budhaditya Hazra, Souvik Chakraborty
A change of measure enhanced near exact Euler Maruyama scheme for the solution to nonlinear stochastic dynamical systems. CoRR (2021)
Akshay Thakur, Souvik Chakraborty
A deep learning based surrogate model for stochastic simulators. CoRR (2021)
Shailesh Garg, Souvik Chakraborty, Budhaditya Hazra
Physics-integrated hybrid framework for model form error identification in nonlinear dynamical systems. CoRR (2021)
Shailesh Garg, Ankush Gogoi, Souvik Chakraborty, Budhaditya Hazra
Machine learning based digital twin for stochastic nonlinear multi-degree of freedom dynamical system. CoRR (2021)
Tapas Tripura, Budhaditya Hazra, Souvik Chakraborty
Generalized weakly corrected Milstein solutions to stochastic differential equations. CoRR (2021)
Sai Krishna Mendu, Souvik Chakraborty
Gated Linear Model induced U-net for surrogate modeling and uncertainty quantification. CoRR (2021)
Navaneeth N., Souvik Chakraborty
Surrogate assisted active subspace and active subspace assisted surrogate - A new paradigm for high dimensional structural reliability analysis. CoRR (2021)
Souvik Chakraborty
Transfer learning based multi-fidelity physics informed deep neural network. J. Comput. Phys. 426 (2021)
Yash Kumar, Souvik Chakraborty
GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations. CoRR (2021)
Yash Kumar, Pranav Bahl, Souvik Chakraborty
State estimation with limited sensors - A deep learning based approach. CoRR (2021)
Souvik Chakraborty, Sondipon Adhikari
Machine learning based digital twin for dynamical systems with multiple time-scales. CoRR (2020)
Souvik Chakraborty, Sondipon Adhikari, Ranjan Ganguli
The role of surrogate models in the development of digital twins of dynamic systems. CoRR (2020)
Souvik Chakraborty
Transfer learning based multi-fidelity physics informed deep neural network. CoRR (2020)
Rajdip Nayek, Souvik Chakraborty, Sriram Narasimhan
A Gaussian process latent force model for joint input-state estimation in linear structural systems. CoRR (2019)
Somdatta Goswami, Cosmin Anitescu, Souvik Chakraborty, Timon Rabczuk
Transfer learning enhanced physics informed neural network for phase-field modeling of fracture. CoRR (2019)
Somdatta Goswami, Souvik Chakraborty, Rajib Chowdhury, Timon Rabczuk
Threshold shift method for reliability-based design optimization. CoRR (2019)
Behrooz Keshtegar, Souvik Chakraborty
Dynamical accelerated performance measure approach for efficient reliability-based design optimization with highly nonlinear probabilistic constraints. Reliab. Eng. Syst. Saf. 178 (2018)
Souvik Chakraborty, Nicholas Zabaras
Efficient data-driven reduced-order models for high-dimensional multiscale dynamical systems. Comput. Phys. Commun. 230 (2018)
Souvik Chakraborty, Dipaloke Majumder
Hybrid Reliability Analysis Framework for Reliability Analysis of Tunnels. J. Comput. Civ. Eng. 32 (4) (2018)
Souvik Chakraborty, Rajib Chowdhury
An efficient algorithm for building locally refined hp - adaptive H-PCFE: Application to uncertainty quantification. J. Comput. Phys. 351 (2017)
Souvik Chakraborty, Rajib Chowdhury
A hybrid approach for global sensitivity analysis. Reliab. Eng. Syst. Saf. 158 (2017)
Souvik Chakraborty, Rajib Chowdhury
Moment Independent Sensitivity Analysis: H-PCFE-Based Approach. J. Comput. Civ. Eng. 31 (1) (2017)
Souvik Chakraborty, Rajib Chowdhury
Modelling uncertainty in incompressible flow simulation using Galerkin based generalized ANOVA. Comput. Phys. Commun. 208 (2016)
Souvik Chakraborty, Rajib Chowdhury
Sequential experimental design based generalised ANOVA. J. Comput. Phys. 317 (2016)