Abstract. Understanding the relationship between connectionist and probabilistic models is important for evaluating the compati- bility of these approaches.

Comparing the inductive biases of simple neural networks and Bayesian models. 2012. Griffiths, Thomas;; Austerweil, Joseph;; Berthiaume, Vincent.

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Comparing the inductive biases of simple neural networks and Bayesian models ... Comparing the inductive biases of simple neural networks and Bayesian models.

Comparing the inductive biases of simple neural networks and Bayesian models. ... Statistical Learning, Inductive Bias, and Bayesian Inference in Language ...

Comparing the inductive biases of simple neural networks and Bayesian models. Proceedings of the 34th Annual Conference of the Cognitive Science Society ...

Researchers have proposed a number of computational models to explain how inductive biases are acquired and har- nessed for future learning. Hierarchical ...

Jul 24, 2024 · In particular, Bayesian models make it easy to explore the inductive biases that inform people's inferences, being those factors other than the ...

May 24, 2023 · We show that learning from limited naturalistic data is possible with an approach that combines the strong inductive biases of a Bayesian model ...

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