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cs.LG2026
Comment on "Modeling rapid language learning by distilling Bayesian priors into artificial neural networks"
Orr Well, Idan Tarshish, Nur Lan +1
McCoy & Griffiths (2025, henceforth M&G) suggest that a Bayesian prior can be distilled into Artificial Neural Networks (ANNs) through Model-Agnostic Meta-Learning (MAML, Finn et a…
cs.LG2025
A Minimum Description Length Approach to Regularization in Neural Networks
Matan Abudy, Orr Well, Emmanuel Chemla +2
State-of-the-art neural networks can be trained to become remarkable solutions to many problems. But while these architectures can express symbolic, perfect solutions, trained mode…
cs.LG2023
Minimum Description Length Hopfield Networks
Matan Abudy, Nur Lan, Emmanuel Chemla +1
Associative memory architectures are designed for memorization but also offer, through their retrieval method, a form of generalization to unseen inputs: stored memories can be see…