Search Results for author: Chris Hill

Found 5 papers, 0 papers with code

A composable machine-learning approach for steady-state simulations on high-resolution grids

no code implementations11 Oct 2022 Rishikesh Ranade, Chris Hill, Lalit Ghule, Jay Pathak

The numerical experiments show that our approach outperforms ML baselines in terms of 1) accuracy across quantitative metrics and 2) generalization to out-of-distribution conditions as well as domain sizes.

A composable autoencoder-based iterative algorithm for accelerating numerical simulations

no code implementations7 Oct 2021 Rishikesh Ranade, Chris Hill, Haiyang He, Amir Maleki, Norman Chang, Jay Pathak

Numerical simulations for engineering applications solve partial differential equations (PDE) to model various physical processes.

BIG-bench Machine Learning

A Latent space solver for PDE generalization

no code implementations6 Apr 2021 Rishikesh Ranade, Chris Hill, Haiyang He, Amir Maleki, Jay Pathak

In this work we propose a hybrid solver to solve partial differential equation (PDE)s in the latent space.

DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization

no code implementations17 May 2020 Rishikesh Ranade, Chris Hill, Jay Pathak

The two solver characteristics that have been adopted in this work are: 1) the use of discretization-based schemes to approximate spatio-temporal partial derivatives and 2) the use of iterative algorithms to solve linearized PDEs in their discrete form.

BIG-bench Machine Learning

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