ML-Assisted Inverse Design
CommunityAutomate CST inverse design with ML surrogates.
AuthorDaryLu0v0
Version1.0.0
Installs0
System Documentation
What problem does it solve?
When CST Tuning stalls, this skill accelerates discovery by auto-generating surrogate models and guiding inverse design with ML, reducing manual iteration.
Core Features & Use Cases
- ML-assisted surrogate training: uses AIDE-enabled design pipelines to auto-create and refine surrogate models.
- Neural Adjoint inverse design: runs neural adjoint optimization to match target spectra with CST simulations for final validation.
- End-to-end workflow: from seed data augmentation to validated designs and reports.
Quick Start
Run the ML-assisted inverse design from a CST project to augment seed data, auto-train a surrogate, and validate top designs with CST simulations.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: ML-Assisted Inverse Design Download link: https://github.com/DaryLu0v0/MetaClaw/archive/main.zip#ml-assisted-inverse-design Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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