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Advanced Scientific Machine Learning

Modern Machine Learning Software
Uncertainty Propagation through Scientific Models
High-dimensional Uncertainty Propagation
- Functional Inputs to Scientific Models
- Operator Learning
Inverse Problems in Deterministic Scientific Models
Inverse Problems in Stochastic Scientific Models
- Stochastic Differential Equations
- Filtering and Smoothing
Physics-informed Neural Networks (PINNs)
Information Field Theory (IFT)

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Differentiable Programming

Contents

Takeaways

Differentiable Programming#

Takeaways#

Automatic differentiation is essential for accelerating machine learning model prototyping.

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Pytrees to represent model parameters

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Numerical Differentiation

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By Ilias Bilionis

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