Yanyan Jin

Learnability Boundary: How Complex Can Neural Networks Learn Pseudo-Random Sequences?

2026 · Zenodo (CERN European Organization for Nuclear Research)

Classical information theory assumes observers have unlimited computational power, making pseudo-random numbers "low entropy." However, for computationally bounded neural networks, the same data may be completely unlearnable noise. This paper experimentally explores the boundary of …