Amortized Hypothesis Generation
Open accessAbstract
Bayesian models of cognition posit that people compute probability distributions over hypotheses, possibly by constructing a sample-based approximation. Since people encounter many closely related distributions, a computationally efficient strategy is to selectively reuse computations – either the samples themselves or some summary statistic. We refer to these reuse strategies as amortized inference . In two experiments, we present evidence consistent with amortization. When sequentially answering two related queries about natural scenes, we show that answers to the second query vary systematically depending on the structure of the first query. Using a cognitive load manipulation, we find evidence that people cache summary statistics rather than raw sample sets. These results enrich our notions of how the brain approximates probabilistic inference.
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Cognitive experiments have revealed signatures of sampling and amortized inference in human behavior.
“In particular, cognitive experiments have revealed signatures of sampling111 and amortized inference112 in human behavior.”
From Cognitive computational neuroscience (2018) · cites this paper as [112]
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- Authors
- Dasgupta, I., Schulz, E., Goodman, N. D., & Gershman, S. J.
- Affiliations
- Harvard University (US)
- University College London (GB)
- Stanford University (US)
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2017-05-12
- OpenAlex
- W2613133638
- Cited by
- 7
- References
- 21
- Citations by year
- 2018: 3 · 2017: 4
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Life Sciences › Neuroscience › Cognitive Neuroscience › Cognitive Science and Education Research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
- Keywords
- amortized inference, hypothesis generation, Bayesian models of cognition, probabilistic inference, summary statistics, cognitive load, natural scene perception
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