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08/11/2022
Gaussian process surrogate models for neural networks
The lack of insight into deep learning systems hinders their systematic ...
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10/08/2021
Distinguishing rule- and exemplar-based generalization in learning systems
Despite the increasing scale of datasets in machine learning, generaliza...
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07/14/2021
Passive attention in artificial neural networks predicts human visual selectivity
Developments in machine learning interpretability techniques over the pa...
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05/15/2021
Are Convolutional Neural Networks or Transformers more like human vision?
Modern machine learning models for computer vision exceed humans in accu...
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11/27/2020
Connecting Context-specific Adaptation in Humans to Meta-learning
Cognitive control, the ability of a system to adapt to the demands of a ...
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06/29/2020
Universal linguistic inductive biases via meta-learning
How do learners acquire languages from the limited data available to the...
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12/14/2018
Online gradient-based mixtures for transfer modulation in meta-learning
Learning-to-learn or meta-learning leverages data-driven inductive bias ...
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08/28/2018
Evaluating Theory of Mind in Question Answering
We propose a new dataset for evaluating question answering models with r...
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01/26/2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes
Meta-learning allows an intelligent agent to leverage prior learning epi...
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02/18/2016
