jkitchin
4 verified skills390 total stars
pycse
Python computations in science and engineering (pycse) - helps with scientific computing tasks including nonlinear regression, uncertainty quantification, design of experiments (DOE), Latin hypercube sampling, surface response modeling, and neural network-based UQ with DPOSE. Use when working with numerical optimization, data fitting, experimental design, or uncertainty analysis.
development276
.claude/skills/jaxsr
# JAXSR Skill — Symbolic Regression Assistant JAXSR is a JAX-based symbolic regression library that discovers interpretable algebraic expressions from data using sparse optimization. It follows ALAMO-style methodology: build a rich candidate basis, then select the simplest model that explains the data. ## Skill Activation Activate this skill when the user wants to: - Discover algebraic expressions or equations from data - Set up a Design of Experiments (DOE) study - Fit, interpret, or export
development38
.claude/skills/jaxsr-review
# JAXSR Review Skill — Red-Team, Engineering & Pedagogical Review Systematically review JAXSR code, documentation, guides, and notebooks for API correctness, engineering quality, and pedagogical clarity. ## Skill Activation Activate this skill when the user invokes `/jaxsr-review` or asks to review, audit, or check correctness of JAXSR-related files (notebooks, guides, templates, source code). ## Invocation Syntax ``` /jaxsr-review <TARGET> # all scopes on one file/
development38
src/jaxsr/skill
# JAXSR Skill — Symbolic Regression Assistant JAXSR is a JAX-based symbolic regression library that discovers interpretable algebraic expressions from data using sparse optimization. It follows ALAMO-style methodology: build a rich candidate basis, then select the simplest model that explains the data. ## Skill Activation Activate this skill when the user wants to: - Discover algebraic expressions or equations from data - Set up a Design of Experiments (DOE) study - Fit, interpret, or export
development38