130 citations · 426 across the 9 of their papers we have counts for
4 papers · 1 filter
Composing Modeling and Simulation with Machine Learning in Julia
Chris Rackauckas, Ranjan Anantharaman, Alan Edelman +10
In this paper we introduce JuliaSim, a high-performance programming environment designed to blend traditional modeling and simulation with machine learning. JuliaSim can build acce…
High-performance symbolic-numerics via multiple dispatch
Shashi Gowda, Yingbo Ma, Alessandro Cheli +4
As mathematical computing becomes more democratized in high-level languages, high-performance symbolic-numeric systems are necessary for domain scientists and engineers to get the…
Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics
Avik Pal, Yingbo Ma, Viral Shah +1
Democratization of machine learning requires architectures that automatically adapt to new problems. Neural Differential Equations (NDEs) have emerged as a popular modeling framewo…
ModelingToolkit: A Composable Graph Transformation System For Equation-Based Modeling
Yingbo Ma, Shashi Gowda, Ranjan Anantharaman +3
Getting good performance out of numerical equation solvers requires that the user has provided stable and efficient functions representing their model. However, users should not be…