polynomial-chaos-expansion

Polynomial chaos for uncertainty propagation

509 stars

Best use case

polynomial-chaos-expansion is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Polynomial chaos for uncertainty propagation

Teams using polynomial-chaos-expansion should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/polynomial-chaos-expansion/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/mathematics/skills/polynomial-chaos-expansion/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/polynomial-chaos-expansion/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How polynomial-chaos-expansion Compares

Feature / Agent	polynomial-chaos-expansion	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Polynomial chaos for uncertainty propagation

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Polynomial Chaos Expansion

## Purpose

Provides polynomial chaos expansion methods for efficient uncertainty propagation in computational models.

## Capabilities

- Generalized polynomial chaos bases
- Sparse PCE construction
- Adaptive basis selection
- PCE-based sensitivity indices
- Low-rank tensor approximation
- Stochastic Galerkin projection

## Usage Guidelines

1. **Basis Selection**: Match basis to input distributions
2. **Truncation**: Choose appropriate polynomial order
3. **Sparsity**: Exploit sparsity for high dimensions
4. **Sensitivity**: Extract Sobol indices from PCE coefficients

## Tools/Libraries

- Chaospy
- UQLab
- OpenTURNS

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