most citedDoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2025

MoWE : A Mixture of Weather Experts

Dibyajyoti Chakraborty, Romit Maulik, Peter Harrington +3

Data-driven weather models have recently achieved state-of-the-art performance, yet progress has plateaued in recent years. This paper introduces a Mixture of Experts (MoWE) approa…

cs.LG2025

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics

Mohammad Amin Nabian, Sanjay Choudhry

The computational cost associated with high-fidelity CFD simulations remains a significant bottleneck in the automotive design and optimization cycle. While ML-based surrogate mode…

cs.LG2025

A Benchmarking Framework for AI models in Automotive Aerodynamics

Kaustubh Tangsali, Rishikesh Ranade, Mohammad Amin Nabian +5

In this paper, we introduce a benchmarking framework within the open-source NVIDIA PhysicsNeMo-CFD framework designed to systematically assess the accuracy, performance, scalabilit…

cs.LG2025

Accelerating Transient CFD through Machine Learning-Based Flow Initialization

Peter Sharpe, Rishikesh Ranade, Kaustubh Tangsali +3

Transient computational fluid dynamics (CFD) simulations are essential for many industrial applications, but suffer from high compute costs relative to steady-state simulations. Th…

cs.LG20252 cited

DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations

Rishikesh Ranade, Mohammad Amin Nabian, Kaustubh Tangsali +4

Numerical simulations play a critical role in design and development of engineering products and processes. Traditional computational methods, such as CFD, can provide accurate pre…