Stochastic Resonance in Neurochaos Learning
-
Updated
May 16, 2021 - Python
Stochastic Resonance in Neurochaos Learning
Hallucination detection and repair for language models, from the orbit partition of a relation. 0.995 AUROC with no ground truth, five proved bounds, and a noise intervention whose level is selected blind.
Computational neuroscience simulation of stochastic resonance in LIF neurons using Python.
Boundary Information Geometry (BIG): boundary-centered reduced models for compact support, finite-time thresholds, fission-like metastability, finite-noise capture, and hidden-depth inheritance.
A tiny, self-contained browser demo that shows why adding **moderate broadband noise** can **improve** detection/recall in a **nonlinear, thresholded** system — and why **lower dopaminergic gain** shifts the optimum to **higher noise**. This is a toy illustration of the **Moderate Brain Arousal (MBA)** idea applied to ADHD.
🧬This repository contains implementations of various bio-inspired optimization algorithms, along with example notebooks and resources for demonstration.
To associate your repository with the stochastic-resonance topic, visit your repo's landing page and select "manage topics."