CrossRef Open Access 2015 1722 sitasi

Human-level concept learning through probabilistic program induction

Brenden M. Lake Ruslan Salakhutdinov Joshua B. Tenenbaum

Abstrak

Handwritten characters drawn by a modelNot only do children learn effortlessly, they do so quickly and with a remarkable ability to use what they have learned as the raw material for creating new stuff. Lakeet al.describe a computational model that learns in a similar fashion and does so better than current deep learning algorithms. The model classifies, parses, and recreates handwritten characters, and can generate new letters of the alphabet that look “right” as judged by Turing-like tests of the model's output in comparison to what real humans produce.Science, this issue p.1332

Penulis (3)

Brenden M. Lake

Ruslan Salakhutdinov

Joshua B. Tenenbaum

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Lake, B.M., Salakhutdinov, R., Tenenbaum, J.B. (2015). Human-level concept learning through probabilistic program induction. https://doi.org/10.1126/science.aab3050

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Informasi Jurnal

Tahun Terbit: 2015
Bahasa: en
Total Sitasi: 1722×
Sumber Database: CrossRef
DOI: 10.1126/science.aab3050
Akses: Open Access ✓