66 citations · 141 across the 6 of their papers we have counts for
8 papers
FlashNeRD: Performance-First Contact-Rich Neural Robot Dynamics
Mohammadmehdi Ataei, Mohammad Amin Nabian, Jie Xu +9
Compared with analytical physics, learned dynamics models promise robot simulation that is faster, inherently differentiable, and easily adaptable to real data. Neural Robot Dynami…
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…
Physics Informed RNN-DCT Networks for Time-Dependent Partial Differential Equations
Benjamin Wu, Oliver Hennigh, Jan Kautz +2
Physics-informed neural networks allow models to be trained by physical laws described by general nonlinear partial differential equations. However, traditional architectures strug…
NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework
Oliver Hennigh, Susheela Narasimhan, Mohammad Amin Nabian +7
We present SimNet, an AI-driven multi-physics simulation framework, to accelerate simulations across a wide range of disciplines in science and engineering. Compared to traditional…
From Deep to Physics-Informed Learning of Turbulence: Diagnostics
Ryan King, Oliver Hennigh, Arvind Mohan +1
We describe tests validating progress made toward acceleration and automation of hydrodynamic codes in the regime of developed turbulence by three Deep Learning (DL) Neural Network…
Automated Design using Neural Networks and Gradient Descent
Oliver Hennigh
We propose a novel method that makes use of deep neural networks and gradient decent to perform automated design on complex real world engineering tasks. Our approach works by trai…
Lat-Net: Compressing Lattice Boltzmann Flow Simulations using Deep Neural Networks
Oliver Hennigh
Computational Fluid Dynamics (CFD) is a hugely important subject with applications in almost every engineering field, however, fluid simulations are extremely computationally and m…
Universal State Transfer on Graphs
Stephen Cameron, Shannon Fehrenbach, Leah Granger +3
A continuous-time quantum walk on a graph is given by the unitary matrix , where is the Hermitian adjacency matrix of . We say has pretty good sta…