[ICML 2026] Code for Equilibrium Reasoners: learning attractor dynamics for scalable reasoning
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Updated
Sep 14, 2026 - Python
[ICML 2026] Code for Equilibrium Reasoners: learning attractor dynamics for scalable reasoning
Detecting field-like memory structures in biological systems - planarian regeneration, bioelectric patterns, and attractor dynamics
Official validator node and mining software client for mining Perseus Coin (PRSC).
One tiny choice. Hundreds of different worlds. A neuro-inspired interactive artwork: delay one spike in a small recurrent network by a few milliseconds, then watch two (and then 1,024) copies of it settle into different interpretations of the same image. Every mind is a real, deterministic simulation.
Code + manuscript: Ring attractor dynamics in mouse ALM. Errors = premature commitment, not noise. DANDI 000060.
Unified Attractor Complexity Model (UACM) 3.0: The Substrate Logic Protocol
neural network trained to remember things briefly, with tools that peek inside it to show it forms stable "memory states" much like real brains do.
100,000 GPU particles flowing through 12 strange attractors in real time. WebGL fragment shaders, ping-pong framebuffers, and chaotic dynamical systems that morph fluidly into one another. Built with p5.js and GLSL.ribes the content specifications for how I want you to make the readme.
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