187 citations · 202 across the 13 of their papers we have counts for
30 papers
PyParSVD: A streaming, distributed and randomized singular-value-decomposition library
Romit Maulik, Gianmarco Mengaldo
We introduce PyParSVD\footnote{https://github.com/Romit-Maulik/PyParSVD}, a Python library that implements a streaming, distributed and randomized algorithm for the singular value…
Data-driven geophysical forecasting: Simple, low-cost, and accurate baselines with kernel methods
Boumediene Hamzi, Romit Maulik, Houman Owhadi
Modeling geophysical processes as low-dimensional dynamical systems and regressing their vector field from data is a promising approach for learning emulators of such systems. We s…
PythonFOAM: In-situ data analyses with OpenFOAM and Python
Romit Maulik, Dimitrios Fytanidis, Bethany Lusch +2
We outline the development of a general-purpose Python-based data analysis tool for OpenFOAM. Our implementation relies on the construction of OpenFOAM applications that have bindi…
Probabilistic neural network-based reduced-order surrogate for fluid flows
Kai Fukami, Romit Maulik, Nesar Ramachandra +2
In recent years, there have been a surge in applications of neural networks (NNs) in physical sciences. Although various algorithmic advances have been proposed, there are, thus fa…
Deploying deep learning in OpenFOAM with TensorFlow
Romit Maulik, Himanshu Sharma, Saumil Patel +2
We outline the development of a data science module within OpenFOAM which allows for the in-situ deployment of trained deep learning architectures for general-purpose predictive ta…
Meta-modeling strategy for data-driven forecasting
Dominic J. Skinner, Romit Maulik
Accurately forecasting the weather is a key requirement for climate change mitigation. Data-driven methods offer the ability to make more accurate forecasts, but lack interpretabil…