Somdatta Goswami
Orcid: 0000-0002-8255-9080
According to our database1,
Somdatta Goswami
authored at least 21 papers
between 2019 and 2024.
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Bibliography
2024
Real-time prediction of gas flow dynamics in diesel engines using a deep neural operator framework.
Appl. Intell., January, 2024
2023
On the influence of over-parameterization in manifold based surrogates and deep neural operators.
J. Comput. Phys., April, 2023
DON-LSTM: Multi-Resolution Learning with DeepONets and Long Short-Term Memory Neural Networks.
CoRR, 2023
Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators.
CoRR, 2023
Developing a cost-effective emulator for groundwater flow modeling using deep neural operators.
CoRR, 2023
CoRR, 2023
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks.
CoRR, 2023
2022
Deep transfer operator learning for partial differential equations under conditional shift.
Nat. Mac. Intell., December, 2022
On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations.
CoRR, 2022
CoRR, 2022
Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms.
CoRR, 2022
Deep transfer learning for partial differential equations under conditional shift with DeepONet.
CoRR, 2022
Learning two-phase microstructure evolution using neural operators and autoencoder architectures.
CoRR, 2022
2021
A robust monolithic solver for phase-field fracture integrated with fracture energy based arc-length method and under-relaxation.
CoRR, 2021
A physics-informed variational DeepONet for predicting the crack path in brittle materials.
CoRR, 2021
2019
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications.
CoRR, 2019
Transfer learning enhanced physics informed neural network for phase-field modeling of fracture.
CoRR, 2019