Somdatta Goswami

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 25

Top Topics

Predictive Accuracy

Transfer Learning

Differential Equations

Top Venues

Nat. Mac. Intell.

J. Comput. Phys.

Publications

Varun Kumar, Somdatta Goswami, Daniel Smith, George Em Karniadakis
Real-time prediction of gas flow dynamics in diesel engines using a deep neural operator framework. Appl. Intell. 54 (1) (2024)
Luis Mandl, Somdatta Goswami, Lena Lambers, Tim Ricken
Separable DeepONet: Breaking the Curse of Dimensionality in Physics-Informed Machine Learning. CoRR (2024)
Qianying Cao, Somdatta Goswami, George Em Karniadakis
Laplace neural operator for solving differential equations. Nat. Mac. Intell. 6 (6) (2024)
Bahador Bahmani, Somdatta Goswami, Ioannis G. Kevrekidis, Michael D. Shields
A Resolution Independent Neural Operator. CoRR (2024)
Maria Luisa Taccari, He Wang, Somdatta Goswami, Jonathan Nuttall, Xiaohui Chen, Peter K. Jimack
Developing a cost-effective emulator for groundwater flow modeling using deep neural operators. CoRR (2023)
Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen
DON-LSTM: Multi-Resolution Learning with DeepONets and Long Short-Term Memory Neural Networks. CoRR (2023)
Katiana Kontolati, Somdatta Goswami, Michael D. Shields, George Em Karniadakis
On the influence of over-parameterization in manifold based surrogates and deep neural operators. J. Comput. Phys. 479 (2023)
Nikolas Borrel-Jensen, Somdatta Goswami, Allan P. Engsig-Karup, George Em Karniadakis, Cheol-Ho Jeong
Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators. CoRR (2023)
Qianying Cao, Somdatta Goswami, George Em Karniadakis
LNO: Laplace Neural Operator for Solving Differential Equations. CoRR (2023)
Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks. CoRR (2023)
Katiana Kontolati, Somdatta Goswami, George Em Karniadakis, Michael D. Shields
Learning in latent spaces improves the predictive accuracy of deep neural operators. CoRR (2023)
Somdatta Goswami, Ameya D. Jagtap, Hessam Babaee, Bryan T. Susi, George Em Karniadakis
Learning stiff chemical kinetics using extended deep neural operators. CoRR (2023)
Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis
Deep transfer operator learning for partial differential equations under conditional shift. Nat. Mac. Intell. 4 (12) (2022)
Katiana Kontolati, Somdatta Goswami, Michael D. Shields, George Em Karniadakis
On the influence of over-parameterization in manifold based surrogates and deep neural operators. CoRR (2022)
Somdatta Goswami, Aniruddha Bora, Yue Yu, George Em Karniadakis
Physics-Informed Deep Neural Operator Networks. CoRR (2022)
Vivek Oommen, Khemraj Shukla, Somdatta Goswami, Rémi Dingreville, George Em Karniadakis
Learning two-phase microstructure evolution using neural operators and autoencoder architectures. CoRR (2022)
Somdatta Goswami, David S. Li, Bruno V. Rego, Marcos Latorre, Jay D. Humphrey, George Em Karniadakis
Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms. CoRR (2022)
Adar Kahana, Enrui Zhang, Somdatta Goswami, George Em Karniadakis, Rishikesh Ranade, Jay Pathak
On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations. CoRR (2022)
Ayan Chakraborty, Cosmin Anitescu, Somdatta Goswami, Xiaoying Zhuang, Timon Rabczuk
Variational energy based XPINNs for phase field analysis in brittle fracture. CoRR (2022)
Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis
Deep transfer learning for partial differential equations under conditional shift with DeepONet. CoRR (2022)
Somdatta Goswami, Minglang Yin, Yue Yu, George E. Karniadakis
A physics-informed variational DeepONet for predicting the crack path in brittle materials. CoRR (2021)
Ritukesh Bharali, Somdatta Goswami, Cosmin Anitescu, Timon Rabczuk
A robust monolithic solver for phase-field fracture integrated with fracture energy based arc-length method and under-relaxation. CoRR (2021)
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)
Esteban Samaniego, Cosmin Anitescu, Somdatta Goswami, Vien Minh Nguyen-Thanh, Hongwei Guo, Khader Hamdia, Timon Rabczuk, Xiaoying Zhuang
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications. CoRR (2019)