1.1k citations · 1.2k across the 5 of their papers we have counts for
5 papers
Learning to correct spectral methods for simulating turbulent flows
Gideon Dresdner, Dmitrii Kochkov, Peter Norgaard +4
Despite their ubiquity throughout science and engineering, only a handful of partial differential equations (PDEs) have analytical, or closed-form solutions. This motivates a vast…
Optimal control of nonequilibrium systems through automatic differentiation
Megan C. Engel, Jamie A. Smith, Michael P. Brenner
Controlling the evolution of nonequilibrium systems to minimize dissipated heat or work is a key goal for designing nanodevices, both in nanotechnology and biology. Progress in com…
Variational Data Assimilation with a Learned Inverse Observation Operator
Thomas Frerix, Dmitrii Kochkov, Jamie A. Smith +3
Variational data assimilation optimizes for an initial state of a dynamical system such that its evolution fits observational data. The physical model can subsequently be evolved i…
Machine learning accelerated computational fluid dynamics
Dmitrii Kochkov, Jamie A. Smith, Ayya Alieva +3
Numerical simulation of fluids plays an essential role in modeling many physical phenomena, such as weather, climate, aerodynamics and plasma physics. Fluids are well described by…
Learning Memory Access Patterns
Milad Hashemi, Kevin Swersky, Jamie A. Smith +5
The explosion in workload complexity and the recent slow-down in Moore's law scaling call for new approaches towards efficient computing. Researchers are now beginning to use recen…