Author

Andrew Heathcote

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#machine learning Preprint Oct 2026

Semi-Amortized Bayesian Inference with Reusable Local Posteriors

A semi-amortized method is introduced that divides parameters into smaller blocks, and uses conditional independence to identify the information needed to infer each block, and trains neural estimators for blocks whose posterior updates are computationally expensive or frequently repeated.

Niek Stevenson, Paul-Christian Burkner, Andrew Heathcote et al. · 0 citations

Open access Aug 2026

Quantifying the effects of prospective memory and ongoing task difficulty on capacity sharing and cognitive control.

This study examines how individuals adapt to varying levels of prospective memory (PM) and ongoing-task difficulty in a cognitively demanding task environment. PM - the ability to remember and execute delayed intentions while engaged in other tasks - depends on flexible allocation of limited-capacity cognitive resource...

Russell J. Boag, L. Strickland, Andrew Heathcote et al. · Memory & Cognition · 0 citations