Brenden M. Lake

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Human-level concept learning through probabilistic program induction

Brenden M. Lake, Ruslan Salakhutdinov, Joshua B. Tenenbaum
Science
2015

People learning new concepts can often generalize successfully from just a single example, yet machine learning algorithms typically require tens or hundreds of examples to perform with similar… (More)

Building Machines That Learn and Think Like People

Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum, Samuel J Gershman
AAMAS
2017

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in… (More)

One shot learning of simple visual concepts

Brenden M. Lake, Ruslan Salakhutdinov, Jason Gross, Joshua B. Tenenbaum
CogSci
2011

People can learn visual concepts from just one encounter, but it remains a mystery how this is accomplished. Many authors have proposed that transferred knowledge from more familiar concepts is a… (More)

Discovering Structure by Learning Sparse Graphs

Brenden M. Lake, Joshua B. Tenenbaum
2010

Systems of concepts such as colors, animals, cities, and artifacts are richly structured, and people discover the structure of these domains throughout a lifetime of experience. Discovering structure… (More)

Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks

Humans can understand and produce new utterances effortlessly, thanks to their compositional skills. Once a person learns the meaning of a new verb “dax,” he or she can immediately understand the… (More)

Still not systematic after all these years: On the compositional skills of sequence-to-sequence recurrent networks

Humans can understand and produce new utterances effortlessly, thanks to their systematic compositional skills. Once a person learns the meaning of a new verb “dax,” he or she can immediately… (More)

Deep Neural Networks Predict Category Typicality Ratings for Images

Brenden M. Lake, Wojciech Zaremba, Rob Fergus, Todd M. Gureckis
CogSci
2015

The latest generation of neural networks has made major performance advances in object categorization from raw images. In particular, deep convolutional neural networks currently outperform… (More)

One-shot learning of generative speech concepts

Brenden M. Lake, Chia-ying Lee, James R. Glass, Joshua B. Tenenbaum
CogSci
2014

One-shot learning – the human ability to learn a new concept from just one or a few examples – poses a challenge to traditional learning algorithms, although approaches based on Hierarchical Bayesian… (More)

Modeling Unsupervised Perceptual Category Learning

Brenden M. Lake, Gautam K. Vallabha, James L. McClelland
IEEE Transactions on Autonomous Mental…
2008

During the learning of speech sounds and other perceptual categories, category labels are not provided, the number of categories is unknown, and the stimuli are encountered sequentially. These… (More)

Estimating the strength of unlabeled information during semi-supervised learning

Semi-supervised category learning is when participants make classification judgements while receiving feedback about the right answers on some trials (labeled stimuli) but not others (unlabeled… (More)

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