Somdatta Goswami

51 papers B 1Journal 50

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Hybrid Conditional Diffusion-DeepONet Framework for High-Fidelity Stress Prediction in Hyperelastic Materials. CoRR Purna Vindhya Kota, Meer Mehran Rashid, Somdatta Goswami, Lori Graham-Brady
2026	J	`jnl`	SPINONet: Scalable Spiking Physics-informed Neural Operator for Computational Mechanics Applications. CoRR Shailesh Garg, Luis Mandl, Somdatta Goswami, Souvik Chakraborty
2025	J	`jnl`	Accelerating Multiscale Modeling with Hybrid Solvers: Coupling FEM and Neural Operators with Domain Decomposition. CoRR Wei Wang, Maryam Hakimzadeh, Haihui Ruan, Somdatta Goswami
2025	J	`jnl`	Data-Efficient Time-Dependent PDE Surrogates: Graph Neural Simulators vs. Neural Operators. CoRR Dibyajyoti Nayak, Somdatta Goswami
2025	J	`jnl`	Efficient Training of Deep Neural Operator Networks via Randomized Sampling. World Sci. Annu. Rev. Artif. Intell. Sharmila Karumuri, Lori Graham-Brady, Somdatta Goswami
2025	J	`jnl`	Enabling Local Neural Operators to perform Equation-Free System-Level Analysis. CoRR Gianluca Fabiani, Hannes Vandecasteele, Somdatta Goswami, Constantinos I. Siettos, Ioannis G. Kevrekidis
2025	J	`jnl`	Enhanced accuracy through ensembling of randomly initialized auto-regressive models for time-dependent PDEs. CoRR Ishan Khurjekar, Indrashish Saha, Lori Graham-Brady, Somdatta Goswami
2025	J	`jnl`	From clutter to clarity: Emergent neural operators via questionnaire metrics. Comput. Chem. Eng. Anastasia S. Georgiou, Arjun Manoj, Pei-Chun Su, Ronald R. Coifman, Ioannis G. Kevrekidis, Somdatta Goswami
2025	J	`jnl`	Importance of localized dilatation and distensibility in identifying determinants of thoracic aortic aneurysm with neural operators. CoRR David S. Li, Somdatta Goswami, Qianying Cao, Vivek Oommen, Roland Assi, Jay D. Humphrey, George E. Karniadakis
2025	J	`jnl`	Importance of localized dilatation and distensibility in identifying determinants of thoracic aortic aneurysm with neural operators. PLoS Comput. Biol. David S. Li, Somdatta Goswami, Qianying Cao, Vivek Oommen, Roland Assi, Jay D. Humphrey, George E. Karniadakis
2025	J	`jnl`	Learning to Control PDEs with Differentiable Predictive Control and Time-Integrated Neural Operators. CoRR Dibakar Roy Sarkar, Ján Drgona, Somdatta Goswami
2025	J	`jnl`	Multi-resolution learning with DeepONets and long short-term memory neural networks. Neurocomputing Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen
2025	J	`jnl`	Neural Operators for Stochastic Modeling of Nonlinear Structural System Response to Natural Hazards. CoRR Somdatta Goswami, Dimitris G. Giovanis, Bowei Li, Seymour M. J. Spence, Michael D. Shields
2025	J	`jnl`	Physics-Informed Latent Neural Operator for Real-time Predictions of Complex Physical Systems. CoRR Sharmila Karumuri, Lori Graham-Brady, Somdatta Goswami
2025	J	`jnl`	Physics-Informed Time-Integrated DeepONet: Temporal Tangent Space Operator Learning for High-Accuracy Inference. CoRR Luis Mandl, Dibyajyoti Nayak, Tim Ricken, Somdatta Goswami
2025	J	`jnl`	Real-Time Brain Biomechanics Prediction with Neural Operators: Toward Clinically Deployable Traumatic Brain Injury Models. CoRR Anusha Agarwal, Dibakar Roy Sarkar, Somdatta Goswami
2025	J	`jnl`	Synergistic learning with multi-task DeepONet for efficient PDE problem solving. Neural Networks Varun Kumar, Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis
2025	J	`jnl`	TI-DeepONet: Learnable Time Integration for Stable Long-Term Extrapolation. CoRR Dibyajyoti Nayak, Somdatta Goswami
2025	J	`jnl`	The Best of Both Worlds: Hybridizing Neural Operators and Solvers for Stable Long-Horizon Inference. CoRR Rajyasri Roy, Dibyajyoti Nayak, Somdatta Goswami
2025	J	`jnl`	UQpy Version 4.2: Uncertainty quantification with Python. SoftwareX Connor Krill, Ponkrshnan Thiagarajan, George D. Pasparakis, Somdatta Goswami, Dimitrios Tsapetis, Dimitris G. Giovanis, Michael D. Shields
2024	J	`jnl`	A Resolution Independent Neural Operator. CoRR Bahador Bahmani, Somdatta Goswami, Ioannis G. Kevrekidis, Michael D. Shields
2024	J	`jnl`	Basis-to-Basis Operator Learning Using Function Encoders. CoRR Tyler Ingebrand, Adam J. Thorpe, Somdatta Goswami, Krishna Kumar, Ufuk Topcu
2024	J	`jnl`	Causality-Respecting Adaptive Refinement for PINNs: Enabling Precise Interface Evolution in Phase Field Modeling. CoRR Wei Wang, Tang Paai Wong, Haihui Ruan, Somdatta Goswami
2024	J	`jnl`	Efficient Training of Deep Neural Operator Networks via Randomized Sampling. CoRR Sharmila Karumuri, Lori Graham-Brady, Somdatta Goswami
2024	J	`jnl`	Laplace neural operator for solving differential equations. Nat. Mac. Intell. Qianying Cao, Somdatta Goswami, George Em Karniadakis
2024	J	`jnl`	Learning Hidden Physics and System Parameters with Deep Operator Networks. CoRR Vijay Kag, Dibakar Roy Sarkar, Birupaksha Pal, Somdatta Goswami
2024	B	`conf`	Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks. IJCNN Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen
2024	J	`jnl`	Real-time prediction of gas flow dynamics in diesel engines using a deep neural operator framework. Appl. Intell. Varun Kumar, Somdatta Goswami, Daniel Smith, George Em Karniadakis
2024	J	`jnl`	Separable DeepONet: Breaking the Curse of Dimensionality in Physics-Informed Machine Learning. CoRR Luis Mandl, Somdatta Goswami, Lena Lambers, Tim Ricken
2024	J	`jnl`	Synergistic Learning with Multi-Task DeepONet for Efficient PDE Problem Solving. CoRR Varun Kumar, Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis
2023	J	`jnl`	DON-LSTM: Multi-Resolution Learning with DeepONets and Long Short-Term Memory Neural Networks. CoRR Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen
2023	J	`jnl`	Developing a cost-effective emulator for groundwater flow modeling using deep neural operators. CoRR Maria Luisa Taccari, He Wang, Somdatta Goswami, Jonathan Nuttall, Xiaohui Chen, Peter K. Jimack
2023	J	`jnl`	LNO: Laplace Neural Operator for Solving Differential Equations. CoRR Qianying Cao, Somdatta Goswami, George Em Karniadakis
2023	J	`jnl`	Learning in latent spaces improves the predictive accuracy of deep neural operators. CoRR Katiana Kontolati, Somdatta Goswami, George Em Karniadakis, Michael D. Shields
2023	J	`jnl`	Learning stiff chemical kinetics using extended deep neural operators. CoRR Somdatta Goswami, Ameya D. Jagtap, Hessam Babaee, Bryan T. Susi, George Em Karniadakis
2023	J	`jnl`	Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks. CoRR Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen
2023	J	`jnl`	On the influence of over-parameterization in manifold based surrogates and deep neural operators. J. Comput. Phys. Katiana Kontolati, Somdatta Goswami, Michael D. Shields, George Em Karniadakis
2023	J	`jnl`	Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators. CoRR Nikolas Borrel-Jensen, Somdatta Goswami, Allan P. Engsig-Karup, George Em Karniadakis, Cheol-Ho Jeong
2022	J	`jnl`	Deep transfer learning for partial differential equations under conditional shift with DeepONet. CoRR Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis
2022	J	`jnl`	Deep transfer operator learning for partial differential equations under conditional shift. Nat. Mac. Intell. Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis
2022	J	`jnl`	Learning two-phase microstructure evolution using neural operators and autoencoder architectures. CoRR Vivek Oommen, Khemraj Shukla, Somdatta Goswami, Rémi Dingreville, George Em Karniadakis
2022	J	`jnl`	Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms. CoRR Somdatta Goswami, David S. Li, Bruno V. Rego, Marcos Latorre, Jay D. Humphrey, George Em Karniadakis
2022	J	`jnl`	On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations. CoRR Adar Kahana, Enrui Zhang, Somdatta Goswami, George Em Karniadakis, Rishikesh Ranade, Jay Pathak
2022	J	`jnl`	On the influence of over-parameterization in manifold based surrogates and deep neural operators. CoRR Katiana Kontolati, Somdatta Goswami, Michael D. Shields, George Em Karniadakis
2022	J	`jnl`	Physics-Informed Deep Neural Operator Networks. CoRR Somdatta Goswami, Aniruddha Bora, Yue Yu, George Em Karniadakis
2022	J	`jnl`	Variational energy based XPINNs for phase field analysis in brittle fracture. CoRR Ayan Chakraborty, Cosmin Anitescu, Somdatta Goswami, Xiaoying Zhuang, Timon Rabczuk
2021	J	`jnl`	A physics-informed variational DeepONet for predicting the crack path in brittle materials. CoRR Somdatta Goswami, Minglang Yin, Yue Yu, George E. Karniadakis
2021	J	`jnl`	A robust monolithic solver for phase-field fracture integrated with fracture energy based arc-length method and under-relaxation. CoRR Ritukesh Bharali, Somdatta Goswami, Cosmin Anitescu, Timon Rabczuk
2019	J	`jnl`	An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications. CoRR Esteban Samaniego, Cosmin Anitescu, Somdatta Goswami, Vien Minh Nguyen-Thanh, Hongwei Guo, Khader M. Hamdia, Timon Rabczuk, Xiaoying Zhuang
2019	J	`jnl`	Threshold shift method for reliability-based design optimization. CoRR Somdatta Goswami, Souvik Chakraborty, Rajib Chowdhury, Timon Rabczuk
2019	J	`jnl`	Transfer learning enhanced physics informed neural network for phase-field modeling of fracture. CoRR Somdatta Goswami, Cosmin Anitescu, Souvik Chakraborty, Timon Rabczuk