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DataDrivenDiffEq.jl is a package for finding systems of equations automatically from a dataset. The methods in this package take in data and return the model which generated the data. A known model is not required as input. These methods can estimate equation-free and equation-based models for discrete, continuous differential equations or direct mappings.
Features
- There are two main types of estimation, depending on if you need the result to be human-understandable
- Structural identification
- Structural estimation
- Human-readable result in symbolic form
- Predicts the derivative and generates a correct time series, but is not necessarily human-readable
- Examples available
Project Samples
Categories
Machine LearningLicense
MIT LicenseFollow DataDrivenDiffEq.jl
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