Author

Jonah W. Brenner

Harvard UniversityORCID 0000-0002-0304-520XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

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Approach:statistical model· 2 Approach:machine learning (classical)· 1

Frequent Co-Authors

Chenguang LiiD· 2 shared Gabriel KreimaniD· 2 shared Adam P. BoeskyiD· 1 shared Sharad RamanathaniD· 1 shared

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2024-2024 · peak 2/yr

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4 top collaborators · 6 mutual co-author links

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2 shared papersNeuroscience

Chenguang LiORCID

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2 papers

Recent·Most cited

NeurosciencebioRxivPreprintNov 1, 2024

Policy optimization emerges from noisy representation learning

Jonah W. Brenner, Chenguang Li, Gabriel Kreiman

This paper introduces a theory where policy optimization emerges from reward-modulated noise in a model of representation learning.

DOI 10.1101/2024.11.01.621621

statistical model

𝕏 PostBluesky

NeurosciencebioRxivPreprintMay 22, 2024

Neuron-level prediction and noise can implement flexible reward-seeking behavior

Chenguang Li, Jonah W. Brenner, Adam P. Boesky…·Gabriel Kreiman

This paper demonstrates that neural networks can exhibit reward-seeking behavior through local predictive updates and internal noise, enabling autonomous and adaptable interaction with environments.

DOI 10.1101/2024.05.22.595306

statistical modelmachine learning (classical)

𝕏 PostBluesky