Romit Maulik

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 59

Top Topics

Machine Learning

Top Venues

J. Comput. Phys.

Mach. Learn. Sci. Technol.

J. Comput. Appl. Math.

Publications

Benjamin Sanderse, Panos Stinis, Romit Maulik, Shady E. Ahmed
Scientific machine learning for closure models in multiscale problems: a review. CoRR (2024)
Dibyajyoti Chakraborty, Seung Whan Chung, Romit Maulik
Divide And Conquer: Learning Chaotic Dynamical Systems With Multistep Penalty Neural Ordinary Differential Equations. CoRR (2024)
Vinamr Jain, Romit Maulik
Higher order quantum reservoir computing for non-intrusive reduced-order models. CoRR (2024)
Tyler Chang, Andrew Gillette, Romit Maulik
Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning. CoRR (2024)
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 (2024)
Katherine Asztalos, René Steijl, Romit Maulik
Reduced-order modeling on a near-term quantum computer. J. Comput. Phys. 510 (2024)
Sunwoong Yang, Hojin Kim, Yoonpyo Hong, Kwanjung Yee, Romit Maulik, Namwoo Kang
Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective. CoRR (2024)
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 (2024)
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 (2024)
Romit Maulik, Romain Egele, Krishnan Raghavan, Prasanna Balaprakash
Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles. CoRR (2023)
Atakan Aygun, Romit Maulik, Ali Karakus
Physics-informed neural networks for mesh deformation with exact boundary enforcement. Eng. Appl. Artif. Intell. 125 (2023)
Deepinder Jot Singh Aulakh, Romit Maulik
Generalizable improvement of the Spalart-Allmaras model through assimilation of experimental data. CoRR (2023)
Varun Shankar, Romit Maulik, Venkatasubramanian Viswanathan
Differentiable Turbulence. CoRR (2023)
Sahil Bhola, Suraj Pawar, Prasanna Balaprakash, Romit Maulik
Multi-fidelity reinforcement learning framework for shape optimization. J. Comput. Phys. 482 (2023)
Varun Shankar, Vedant Puri, Ramesh Balakrishnan, Romit Maulik, Venkatasubramanian Viswanathan
Differentiable physics-enabled closure modeling for Burgers' turbulence. Mach. Learn. Sci. Technol. 4 (1) (2023)
Shivam Barwey, Varun Shankar, Venkatasubramanian Viswanathan, Romit Maulik
Multiscale Graph Neural Network Autoencoders for Interpretable Scientific Machine Learning. CoRR (2023)
Shivam Barwey, Romit Maulik
Interpretable Fine-Tuning for Graph Neural Network Surrogate Models. CoRR (2023)
Jonah Botvinick-Greenhouse, Yunan Yang, Romit Maulik
Generative Modeling of Time-Dependent Densities via Optimal Transport and Projection Pursuit. CoRR (2023)
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 (2023)
Shivam Barwey, Varun Shankar, Venkatasubramanian Viswanathan, Romit Maulik
Multiscale graph neural network autoencoders for interpretable scientific machine learning. J. Comput. Phys. 495 (2023)
Varun Shankar, Shivam Barwey, Zico Kolter, Romit Maulik, Venkatasubramanian Viswanathan
Importance of equivariant and invariant symmetries for fluid flow modeling. CoRR (2023)
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 (2023)
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 (2023)
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 (2023)
Varun Shankar, Romit Maulik, Venkatasubramanian Viswanathan
Differentiable Turbulence II. CoRR (2023)
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 (2022)
Varun Shankar, Vedant Puri, Ramesh Balakrishnan, Romit Maulik, Venkatasubramanian Viswanathan
Differentiable physics-enabled closure modeling for Burgers' turbulence. CoRR (2022)
Romit Maulik, Dimitrios Fytanidis, Bethany Lusch, Venkatram Vishwanath, Saumil Patel
PythonFOAM: In-situ data analyses with OpenFOAM and Python. J. Comput. Sci. 62 (2022)
Romain Egele, Romit Maulik, Krishnan Raghavan, Bethany Lusch, Isabelle Guyon, Prasanna Balaprakash
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification. ICPR (2022)
Coleman Moss, Romit Maulik, Giacomo Valerio Iungo
Modeling Wind Turbine Performance and Wake Interactions with Machine Learning. CoRR (2022)
Sahil Bhola, Suraj Pawar, Prasanna Balaprakash, Romit Maulik
Multi-fidelity reinforcement learning framework for shape optimization. CoRR (2022)
Andrea Lario, Romit Maulik, Oliver T. Schmidt, Gianluigi Rozza, Gianmarco Mengaldo
Neural-network learning of SPOD latent dynamics. J. Comput. Phys. 468 (2022)
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) (2022)
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) (2022)
Suraj Pawar, Romit Maulik
Distributed deep reinforcement learning for simulation control. Mach. Learn. Sci. Technol. 2 (2) (2021)
Gianmarco Mengaldo, Romit Maulik
PySPOD: A Python package for Spectral Proper Orthogonal Decomposition (SPOD). J. Open Source Softw. 6 (60) (2021)
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) (2021)
Romit Maulik, Gianmarco Mengaldo
PyParSVD: A streaming, distributed and randomized singular-value-decomposition library. DRBSD@SC (2021)
Andrea Lario, Romit Maulik, Gianluigi Rozza, Gianmarco Mengaldo
Neural-network learning of SPOD latent dynamics. CoRR (2021)
Romain Egele, Romit Maulik, Krishnan Raghavan, Prasanna Balaprakash, Bethany Lusch
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification. CoRR (2021)
S. Ashwin Renganathan, Romit Maulik, Stefano Letizia, Giacomo Valerio Iungo
Data-Driven Wind Turbine Wake Modeling via Probabilistic Machine Learning. CoRR (2021)
Romit Maulik, Dimitrios Fytanidis, Bethany Lusch, Venkatram Vishwanath, Saumil Patel
PythonFOAM: In-situ data analyses with OpenFOAM and Python. CoRR (2021)
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)
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 (2021)
Romit Maulik, Gianmarco Mengaldo
PyParSVD: A streaming, distributed and randomized singular-value-decomposition library. CoRR (2021)
Kai Fukami, Romit Maulik, Nesar Ramachandra, Koji Fukagata, Kunihiko Taira
Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning. CoRR (2021)
Yubin Lu, Romit Maulik, Ting Gao, Felix Dietrich, Ioannis G. Kevrekidis, Jinqiao Duan
Learning the temporal evolution of multivariate densities via normalizing flows. CoRR (2021)
Romit Maulik, Romain Egele, Bethany Lusch, Prasanna Balaprakash
Recurrent neural network architecture search for geophysical emulation. SC (2020)
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 (2020)
Dominic J. Skinner, Romit Maulik
Meta-modeling strategy for data-driven forecasting. CoRR (2020)
Romit Maulik, Rajeev Surendran Array, Prasanna Balaprakash
Site-specific graph neural network for predicting protonation energy of oxygenate molecules. CoRR (2020)
Romit Maulik, Himanshu Sharma, Saumil Patel, Bethany Lusch, Elise Jennings
Deploying deep learning in OpenFOAM with TensorFlow. CoRR (2020)
Vishwas Rao, Romit Maulik, Emil M. Constantinescu, Mihai Anitescu
A Machine-Learning-Based Importance Sampling Method to Compute Rare Event Probabilities. ICCS (6) (2020)
Romit Maulik, Omer San
Numerical assessments of a parametric implicit large eddy simulation model. J. Comput. Appl. Math. 376 (2020)
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 (2019)
Omer San, Romit Maulik, Mansoor Ahmed
An artificial neural network framework for reduced order modeling of transient flows. Commun. Nonlinear Sci. Numer. Simul. 77 (2019)
Romit Maulik, Omer San
Explicit and implicit LES closures for Burgers turbulence. J. Comput. Appl. Math. 327 (2018)
Omer San, Romit Maulik
Neural network closures for nonlinear model order reduction. Adv. Comput. Math. 44 (6) (2018)
Romit Maulik, Omer San
A novel dynamic framework for subgrid scale parametrization of mesoscale eddies in quasigeostrophic turbulent flows. Comput. Math. Appl. 74 (3) (2017)