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Found 2 papers, 1 papers with code
Efficient Sampling-Based Bayesian Active Learning for synaptic characterization
Bayesian Active Learning (BAL) is an efficient framework for learning the parameters of a model, in which input stimuli are selected to maximize the mutual information between the observations and the unknown parameters.
DELAUNAY: a dataset of abstract art for psychophysical and machine learning research
This dataset provides a middle ground between natural images and artificial patterns and can thus be used in a variety of contexts, for example to investigate the sample efficiency of humans and artificial neural networks.
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