From the 2 of 5 linked papers with an AI index.
5 papers
What Makes a Representational Prior Work? Feature Families, Label-Free Invariances, and Critical Windows in Grokking
Gunner Levi Howe
The paper investigates why certain representational priors speed up the delayed generalization phenomenon known as grokking, showing that feature‑family alignment, label‑free invar…
Structure-Specific Representational Priors Causally Control the Grokking Delay
Gunner Levi Howe
The paper experimentally shows that the delayed generalization known as grokking is caused by the time needed to form task‑specific representations, using injected representational…
Intrinsic-Noise Consolidation: A Doob-Barrier-Conditioned Diffusion Turns Analog Device Noise into a Continual-Learning Resource
Gunner Levi Howe
On analog neuromorphic hardware, intrinsic device noise is normally an accuracy tax. We ask whether it can instead consolidate memories. We cast per-synapse consolidation as a Doob…
Level-Crossing Density as a Mesh-Free High-Frequency Auxiliary Loss for Implicit Neural Representations
Gunner Levi Howe
The Minkowski functionals of a field's excursion sets -- area, boundary measure, and Euler characteristic -- describe its level-set morphology; the Euler characteristic is the chea…
Heckman-Corrected Epistemic Uncertainty: Selection on Unobservables Defeats Importance Weighting
Gunner Levi Howe
Training data for machine learning is routinely collected by a selection process the model never sees: loans are observed only when granted, outcomes only when a test was ordered.…