langevin-dynamics

Official

Bridge theory to practice in SDE learning.

Authorplurigrid
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Langevin dynamics are used to study neural network learning by injecting controlled noise to analyze exploration, convergence, and discretization effects in training dynamics.

Core Features & Use Cases

  • Solve Langevin SDEs: compare multiple discretization solvers.
  • Fokker-Planck convergence: empirically verify proximity to Gibbs distribution.
  • Mixing time estimation: evaluate when training equilibrates.
  • Temperature effects: study how noise level influences exploration vs exploitation.
  • Discretization study: observe how different dt alter results.

Quick Start

just langevin-solve net=logistic T=0.01 dt=0.01

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: langevin-dynamics
Download link: https://github.com/plurigrid/asi/archive/main.zip#langevin-dynamics

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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