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08/19/2020
A new role for circuit expansion for learning in neural networks
Many sensory pathways in the brain rely on sparsely active populations o...
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06/02/2019
Dimensionality compression and expansion in Deep Neural Networks
Datasets such as images, text, or movies are embedded in high-dimensiona...
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06/03/2018
Minnorm training: an algorithm for training over-parameterized deep neural networks
In this work, we propose a new training method for finding minimum weigh...
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06/03/2018
Minnorm training: an algorithm for training overcomplete deep neural networks
In this work, we propose a new training method for finding minimum weigh...
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09/22/2016
An equivalence between high dimensional Bayes optimal inference and M-estimation
When recovering an unknown signal from noisy measurements, the computati...
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01/18/2016
Statistical Mechanics of High-Dimensional Inference
To model modern large-scale datasets, we need efficient algorithms to in...
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01/30/2013