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2020 – today
- 2025
[j20]Tyler H. Chang
, Andrew Gillette, Romit Maulik:
Leveraging interpolation models and error bounds for verifiable scientific machine learning. J. Comput. Phys. 524: 113726 (2025)- [c8]Hong Zhang, Ying Liu, Romit Maulik:
Semi-Implicit Neural Ordinary Differential Equations. AAAI 2025: 22416-22424 - [i44]Dibyajyoti Chakraborty, Arvind T. Mohan, Romit Maulik:
Binned Spectral Power Loss for Improved Prediction of Chaotic Systems. CoRR abs/2502.00472 (2025) - [i43]Xin Wang, Juntao Yang, Jeff Adie, Simon See, Kalli Furtado, Chen Chen, Troy Arcomano, Romit Maulik, Gianmarco Mengaldo:
CondensNet: Enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints. CoRR abs/2502.13185 (2025) - [i42]Xuyang Li, Romit Maulik:
SALSA-RL: Stability Analysis in the Latent Space of Actions for Reinforcement Learning. CoRR abs/2502.15512 (2025) - 2024
- [j19]Marcin Rogowski, Brandon C. Y. Yeung, Oliver T. Schmidt, Romit Maulik, Lisandro Dalcín, Matteo Parsani, Gianmarco Mengaldo:
Unlocking massively parallel spectral proper orthogonal decompositions in the PySPOD package. Comput. Phys. Commun. 302: 109246 (2024) - [j18]Katherine Asztalos, René Steijl, Romit Maulik:
Reduced-order modeling on a near-term quantum computer. J. Comput. Phys. 510: 113070 (2024) - [c7]Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Romit Maulik, Rao Kotamarthi, Ian T. Foster, Sandeep Madireddy, Aditya Grover:
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. NeurIPS 2024 - [c6]Shivam Barwey, Riccardo Balin, Bethany Lusch, Saumil Patel, Ramesh Balakrishnan, Pinaki Pal, Romit Maulik, Venkatram Vishwanath:
Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling. SC Workshops 2024: 1058-1070 - [i41]Sunwoong Yang, Hojin Kim, Yoonpyo Hong, Kwanjung Yee, Romit Maulik, Namwoo Kang:
Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective. CoRR abs/2401.08667 (2024) - [i40]Benjamin Sanderse, Panos Stinis, Romit Maulik, Shady E. Ahmed:
Scientific machine learning for closure models in multiscale problems: a review. CoRR abs/2403.02913 (2024) - [i39]Tyler H. Chang, Andrew Gillette, Romit Maulik:
Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning. CoRR abs/2404.03586 (2024) - [i38]Haiwen Guan, Troy Arcomano, Ashesh Chattopadhyay, Romit Maulik:
LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability and physical consistency for O(1000)-member ensembles. CoRR abs/2405.16297 (2024) - [i37]Dibyajyoti Chakraborty, Shivam Barwey, Hong Zhang, Romit Maulik:
A note on the error analysis of data-driven closure models for large eddy simulations of turbulence. CoRR abs/2405.17612 (2024) - [i36]Dibyajyoti Chakraborty, Seung Whan Chung, Romit Maulik:
Divide And Conquer: Learning Chaotic Dynamical Systems With Multistep Penalty Neural Ordinary Differential Equations. CoRR abs/2407.00568 (2024) - [i35]Vinamr Jain, Romit Maulik:
Higher order quantum reservoir computing for non-intrusive reduced-order models. CoRR abs/2407.21602 (2024) - [i34]Shivam Barwey, Pinaki Pal, Saumil Patel, Riccardo Balin, Bethany Lusch, Venkatram Vishwanath, Romit Maulik, Ramesh Balakrishnan:
Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks. CoRR abs/2409.07769 (2024) - [i33]Jonah Botvinick-Greenhouse, Maria Oprea, Romit Maulik, Yunan Yang:
Measure-Theoretic Time-Delay Embedding. CoRR abs/2409.08768 (2024) - [i32]Zachariah Malik, Romit Maulik:
A competitive baseline for deep learning enhanced data assimilation using conditional Gaussian ensemble Kalman filtering. CoRR abs/2409.14300 (2024) - [i31]Shivam Barwey, Riccardo Balin, Bethany Lusch, Saumil Patel, Ramesh Balakrishnan, Pinaki Pal, Romit Maulik, Venkatram Vishwanath:
Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling. CoRR abs/2410.01657 (2024) - [i30]Dibyajyoti Chakraborty, Seung Whan Chung, Ashesh Chattopadhyay, Romit Maulik:
Improved deep learning of chaotic dynamical systems with multistep penalty losses. CoRR abs/2410.05572 (2024) - [i29]Hong Zhang, Ying Liu, Romit Maulik:
Semi-Implicit Neural Ordinary Differential Equations. CoRR abs/2412.11301 (2024) - 2023
- [j17]Atakan Aygun, Romit Maulik, Ali Karakus:
Physics-informed neural networks for mesh deformation with exact boundary enforcement. Eng. Appl. Artif. Intell. 125: 106660 (2023) - [j16]Alec J. Linot, Joshua W. Burby, Qi Tang, Prasanna Balaprakash, Michael D. Graham, Romit Maulik:
Stabilized neural ordinary differential equations for long-time forecasting of dynamical systems. J. Comput. Phys. 474: 111838 (2023) - [j15]Sahil Bhola, Suraj Pawar, Prasanna Balaprakash, Romit Maulik:
Multi-fidelity reinforcement learning framework for shape optimization. J. Comput. Phys. 482: 112018 (2023) - [j14]Shivam Barwey, Varun Shankar, Venkatasubramanian Viswanathan, Romit Maulik:
Multiscale graph neural network autoencoders for interpretable scientific machine learning. J. Comput. Phys. 495: 112537 (2023) - [j13]Varun Shankar, Vedant Puri, Ramesh Balakrishnan, Romit Maulik, Venkatasubramanian Viswanathan:
Differentiable physics-enabled closure modeling for Burgers' turbulence. Mach. Learn. Sci. Technol. 4(1): 15017 (2023) - [i28]Shivam Barwey, Varun Shankar, Venkatasubramanian Viswanathan, Romit Maulik:
Multiscale Graph Neural Network Autoencoders for Interpretable Scientific Machine Learning. CoRR abs/2302.06186 (2023) - [i27]Romit Maulik, Romain Egele, Krishnan Raghavan, Prasanna Balaprakash:
Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles. CoRR abs/2302.09748 (2023) - [i26]Jonah Botvinick-Greenhouse, Yunan Yang, Romit Maulik:
Generative Modeling of Time-Dependent Densities via Optimal Transport and Projection Pursuit. CoRR abs/2304.09663 (2023) - [i25]Varun Shankar, Romit Maulik, Venkatasubramanian Viswanathan:
Differentiable Turbulence. CoRR abs/2307.03683 (2023) - [i24]Varun Shankar, Shivam Barwey, Zico Kolter, Romit Maulik, Venkatasubramanian Viswanathan:
Importance of equivariant and invariant symmetries for fluid flow modeling. CoRR abs/2307.05486 (2023) - [i23]Varun Shankar, Romit Maulik, Venkatasubramanian Viswanathan:
Differentiable Turbulence II. CoRR abs/2307.13533 (2023) - [i22]Deepinder Jot Singh Aulakh, Romit Maulik:
Generalizable improvement of the Spalart-Allmaras model through assimilation of experimental data. CoRR abs/2309.06679 (2023) - [i21]Marcin Rogowski, Brandon C. Y. Yeung, Oliver T. Schmidt, Romit Maulik, Lisandro Dalcín, Matteo Parsani, Gianmarco Mengaldo:
Unlocking massively parallel spectral proper orthogonal decompositions in the PySPOD package. CoRR abs/2309.11808 (2023) - [i20]Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens:
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR abs/2310.04610 (2023) - [i19]Shivam Barwey, Romit Maulik:
Interpretable Fine-Tuning for Graph Neural Network Surrogate Models. CoRR abs/2311.07548 (2023) - [i18]Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Sandeep Madireddy, Romit Maulik, Veerabhadra Kotamarthi, Ian T. Foster, Aditya Grover:
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. CoRR abs/2312.03876 (2023) - 2022
- [j12]Andrea Lario, Romit Maulik, Oliver T. Schmidt, Gianluigi Rozza, Gianmarco Mengaldo:
Neural-network learning of SPOD latent dynamics. J. Comput. Phys. 468: 111475 (2022) - [j11]Romit Maulik, Dimitrios Fytanidis, Bethany Lusch, Venkatram Vishwanath, Saumil Patel:
PythonFOAM: In-situ data analyses with OpenFOAM and Python. J. Comput. Sci. 62: 101750 (2022) - [j10]Nathan A Garland, Romit Maulik, Qi Tang, Xian-Zhu Tang, Prasanna Balaprakash:
Efficient data acquisition and training of collisional-radiative model artificial neural network surrogates through adaptive parameter space sampling. Mach. Learn. Sci. Technol. 3(4): 45003 (2022) - [j9]S. Ashwin Renganathan, Romit Maulik, Stefano Letizia, Giacomo Valerio Iungo:
Data-driven wind turbine wake modeling via probabilistic machine learning. Neural Comput. Appl. 34(8): 6171-6186 (2022) - [c5]Romain Egele, Romit Maulik, Krishnan Raghavan, Bethany Lusch, Isabelle Guyon, Prasanna Balaprakash:
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification. ICPR 2022: 1908-1914 - [i17]Sahil Bhola, Suraj Pawar, Prasanna Balaprakash, Romit Maulik:
Multi-fidelity reinforcement learning framework for shape optimization. CoRR abs/2202.11170 (2022) - [i16]Alec J. Linot, Joshua W. Burby, Qi Tang, Prasanna Balaprakash, Michael D. Graham, Romit Maulik:
Stabilized Neural Ordinary Differential Equations for Long-Time Forecasting of Dynamical Systems. CoRR abs/2203.15706 (2022) - [i15]Varun Shankar, Vedant Puri, Ramesh Balakrishnan, Romit Maulik, Venkatasubramanian Viswanathan:
Differentiable physics-enabled closure modeling for Burgers' turbulence. CoRR abs/2209.11614 (2022) - [i14]Coleman Moss, Romit Maulik, Giacomo Valerio Iungo:
Modeling Wind Turbine Performance and Wake Interactions with Machine Learning. CoRR abs/2212.01483 (2022) - 2021
- [j8]Gianmarco Mengaldo, Romit Maulik:
PySPOD: A Python package for Spectral Proper Orthogonal Decomposition (SPOD). J. Open Source Softw. 6(60): 2862 (2021) - [j7]Suraj Pawar, Romit Maulik:
Distributed deep reinforcement learning for simulation control. Mach. Learn. Sci. Technol. 2(2): 25029 (2021) - [j6]Kai Fukami, Romit Maulik, Nesar Ramachandra, Koji Fukagata, Kunihiko Taira:
Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning. Nat. Mach. Intell. 3(11): 945-951 (2021) - [c4]Varuni Katti Sastry, Romit Maulik, Vishwas Rao, Bethany Lusch, S. Ashwin Renganathan, Rao Kotamarthi:
Data-Driven Deep Learning Emulators for Geophysical Forecasting. ICCS (5) 2021: 433-446 - [c3]Romit Maulik, Gianmarco Mengaldo:
PyParSVD: A streaming, distributed and randomized singular-value-decomposition library. DRBSD@SC 2021: 19-25 - [i13]Kai Fukami, Romit Maulik, Nesar Ramachandra, Koji Fukagata, Kunihiko Taira:
Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning. CoRR abs/2101.00554 (2021) - [i12]Romit Maulik, Dimitrios Fytanidis, Bethany Lusch, Venkatram Vishwanath, Saumil Patel:
PythonFOAM: In-situ data analyses with OpenFOAM and Python. CoRR abs/2103.09389 (2021) - [i11]Yubin Lu, Romit Maulik, Ting Gao, Felix Dietrich, Ioannis G. Kevrekidis, Jinqiao Duan:
Learning the temporal evolution of multivariate densities via normalizing flows. CoRR abs/2107.13735 (2021) - [i10]Romit Maulik, Gianmarco Mengaldo:
PyParSVD: A streaming, distributed and randomized singular-value-decomposition library. CoRR abs/2108.08845 (2021) - [i9]S. Ashwin Renganathan, Romit Maulik, Stefano Letizia, Giacomo Valerio Iungo:
Data-Driven Wind Turbine Wake Modeling via Probabilistic Machine Learning. CoRR abs/2109.02411 (2021) - [i8]Masaki Morimoto, Kai Fukami, Romit Maulik, Ricardo Vinuesa, Koji Fukagata:
Assessments of model-form uncertainty using Gaussian stochastic weight averaging for fluid-flow regression. CoRR abs/2109.08248 (2021) - [i7]Andrea Lario, Romit Maulik, Gianluigi Rozza, Gianmarco Mengaldo:
Neural-network learning of SPOD latent dynamics. CoRR abs/2110.09218 (2021) - [i6]Romain Egele, Romit Maulik, Krishnan Raghavan, Prasanna Balaprakash, Bethany Lusch:
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification. CoRR abs/2110.13511 (2021) - 2020
- [j5]Romit Maulik, Omer San:
Numerical assessments of a parametric implicit large eddy simulation model. J. Comput. Appl. Math. 376: 112866 (2020) - [c2]Vishwas Rao, Romit Maulik, Emil M. Constantinescu, Mihai Anitescu:
A Machine-Learning-Based Importance Sampling Method to Compute Rare Event Probabilities. ICCS (6) 2020: 169-182 - [c1]Romit Maulik, Romain Egele, Bethany Lusch, Prasanna Balaprakash:
Recurrent neural network architecture search for geophysical emulation. SC 2020: 8 - [i5]Romit Maulik, Rajeev Surendran Array, Prasanna Balaprakash:
Site-specific graph neural network for predicting protonation energy of oxygenate molecules. CoRR abs/2001.03136 (2020) - [i4]Romit Maulik, Themistoklis Botsas, Nesar Ramachandra, Lachlan Robert Mason, Indranil Pan:
Latent-space time evolution of non-intrusive reduced-order models using Gaussian process emulation. CoRR abs/2007.12167 (2020) - [i3]Dominic J. Skinner, Romit Maulik:
Meta-modeling strategy for data-driven forecasting. CoRR abs/2012.00678 (2020) - [i2]Romit Maulik, Himanshu Sharma, Saumil Patel, Bethany Lusch, Elise Jennings:
Deploying deep learning in OpenFOAM with TensorFlow. CoRR abs/2012.00900 (2020)
2010 – 2019
- 2019
- [j4]Omer San, Romit Maulik, Mansoor Ahmed:
An artificial neural network framework for reduced order modeling of transient flows. Commun. Nonlinear Sci. Numer. Simul. 77: 271-287 (2019) - [i1]Romit Maulik, Vishwas Rao, Sandeep Madireddy, Bethany Lusch, Prasanna Balaprakash:
Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models. CoRR abs/1909.09144 (2019) - 2018
- [j3]Omer San, Romit Maulik:
Neural network closures for nonlinear model order reduction. Adv. Comput. Math. 44(6): 1717-1750 (2018) - [j2]Romit Maulik, Omer San:
Explicit and implicit LES closures for Burgers turbulence. J. Comput. Appl. Math. 327: 12-40 (2018) - 2017
- [j1]Romit Maulik, Omer San:
A novel dynamic framework for subgrid scale parametrization of mesoscale eddies in quasigeostrophic turbulent flows. Comput. Math. Appl. 74(3): 420-445 (2017)
Coauthor Index
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last updated on 2025-06-02 01:30 CEST by the dblp team
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