About
This skill enables gradient-free optimization using discrete {-1, 0, +1} perturbations instead of continuous gradients. It's designed for non-differentiable functions like hash lookups, quantized networks, and combinatorial optimization problems. Developers should use it when working with systems where traditional gradient-based learning is impossible or ineffective.
Quick Install
Claude Code
Recommendednpx skills add plurigrid/asi -a claude-code/plugin add https://github.com/plurigrid/asigit clone https://github.com/plurigrid/asi.git ~/.claude/skills/discrete-backpropCopy and paste this command in Claude Code to install this skill
GitHub Repository
Frequently asked questions
What is the discrete-backprop skill?
discrete-backprop is a Claude Skill by plurigrid. Skills package instructions and resources that Claude loads on demand, so Claude can perform discrete-backprop-related tasks without extra prompting.
How do I install discrete-backprop?
Use the install commands on this page: add discrete-backprop to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does discrete-backprop belong to?
discrete-backprop is in the Other category, tagged general.
Is discrete-backprop free to use?
Yes. discrete-backprop is listed on AIMCP and free to install. It runs inside Claude, so no separate service account is required to use the skill itself.
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