[HTML][HTML] Machine learning interpretability: A survey on methods and metrics

DV Carvalho, EM Pereira, JS Cardoso - Electronics, 2019 - mdpi.com
Background: Open Access Editor's Choice Review Machine Learning Interpretability: A
Survey on Methods and Metrics by Diogo V. Carvalho 1, 2,*, Eduardo M. Pereira 1 and …

The relational bottleneck as an inductive bias for efficient abstraction

TW Webb, SM Frankland, A Altabaa, S Segert… - Trends in Cognitive …, 2024 - cell.com
A central challenge for cognitive science is to explain how abstract concepts are acquired
from limited experience. This has often been framed in terms of a dichotomy between …

The best game in town: The reemergence of the language-of-thought hypothesis across the cognitive sciences

J Quilty-Dunn, N Porot, E Mandelbaum - Behavioral and Brain …, 2023 - cambridge.org
Mental representations remain the central posits of psychology after many decades of
scrutiny. However, there is no consensus about the representational format (s) of biological …

Neuro-symbolic artificial intelligence: a survey

BP Bhuyan, A Ramdane-Cherif, R Tomar… - Neural Computing and …, 2024 - Springer
The goal of the growing discipline of neuro-symbolic artificial intelligence (AI) is to develop
AI systems with more human-like reasoning capabilities by combining symbolic reasoning …

Generative linguistics and neural networks at 60: Foundation, friction, and fusion

J Pater - Language, 2019 - muse.jhu.edu
The birthdate of both generative linguistics and neural networks can be taken as 1957, the
year of the publication of foundational work by both Noam Chomsky and Frank Rosenblatt …