JuliaCon Local Paris 2025

Universal Differential Equations (or UDEs for short) have emerged as a novel way to integrate information
from experimental data into mechanistic models. In this talk I will present ModelingToolkitNeuralNets, a package intended to help with embedding neural networks inside ModelingToolkit models.

Model Discovery is a symbolic-numeric method that modifies the physical equations of a dynamic system in order to fit test or telemetry data. In this talk, we introduce the Model Discovery pipeline in the Julia product Dyad, which builds upon Universal Differential Equations and other SciML methods.