التفاصيل البيبلوغرافية
| العنوان: |
Meta-learning as a bridge between neural networks and symbolic Bayesian models. |
| المؤلفون: |
McCoy RT; Department of Linguistics, Yale University, New Haven, CT, USA tom.mccoy@yale.eduhttps://rtmccoy.com/., Griffiths TL; Departments of Psychology and Computer Science, Princeton University, Princeton, NJ, USA tomg@princeton.eduhttp://cocosci.princeton.edu/tom/. |
| المصدر: |
The Behavioral and brain sciences [Behav Brain Sci] 2024 Sep 23; Vol. 47, pp. e155. Date of Electronic Publication: 2024 Sep 23. |
| نوع المنشور: |
Journal Article |
| اللغة: |
English |
| بيانات الدورية: |
Publisher: Cambridge Univ. Press Country of Publication: England NLM ID: 7808666 Publication Model: Electronic Cited Medium: Internet ISSN: 1469-1825 (Electronic) Linking ISSN: 0140525X NLM ISO Abbreviation: Behav Brain Sci Subsets: MEDLINE |
| أسماء مطبوعة: |
Original Publication: Cambridge [Eng.], New York, Cambridge Univ. Press. |
| مواضيع طبية MeSH: |
Bayes Theorem* , Neural Networks, Computer* , Learning*/physiology, Humans |
| مستخلص: |
Meta-learning is even more broadly relevant to the study of inductive biases than Binz et al. suggest: Its implications go beyond the extensions to rational analysis that they discuss. One noteworthy example is that meta-learning can act as a bridge between the vector representations of neural networks and the symbolic hypothesis spaces used in many Bayesian models. |
| تواريخ الأحداث: |
Date Created: 20240923 Date Completed: 20240923 Latest Revision: 20240923 |
| رمز التحديث: |
20240923 |
| DOI: |
10.1017/S0140525X24000116 |
| PMID: |
39311528 |
| قاعدة البيانات: |
MEDLINE |
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