JuliaSim: Machine Learning Accelerated Modeling and Simulation

Explore machine learning accelerated modeling and simulation in this 30-minute JuliaCon2021 talk by Chris Rackauckas. Dive into the industrial applications of Julia, fast differential equation solvers, and the integration of neural networks. Learn about the SciML ecosystem and its coverage, as well as the introduction of JuliaSim. Discover next-generation algorithms, acceleration via surrogates, and composed surrogates. Gain insights into training surrogates with JuliaHub, pretrained models, and the GUI. Examine examples of JuliaSim integration and its roadmap. By the end, understand how to leverage Julia's speed and machine learning capabilities to optimize modeling and simulation processes.

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Industrial application of Julia.
Fast Differential Equation Solvers.
Speedup of symbolic computation.
Integration with neural networks.
Engineering a Community.
SciML coverage.
Missing pieces in SciML.
JuliaSim introduction.
Next generation of algorithms.
Acceleration via surrogates.
Composed surrogates.
Training surrogates with JuliaHub.
Pretrained models.
GUI.
Examples of JuliaSim integration.
JuliaSim Roadmap.
Try JuliaSim.