Training deep neural density estimators to identify mechanistic models of 
neural dynamics

Gonçalves, Pedro J.; Lueckmann, Jan-Matthis; Deistler, Michael; Nonnenmacher, Marcel; Öcal, Kaan; Bassetto, Giacomo; Chintaluri, Chaitanya; Podlaski, William F.; Haddad, Sara A.; Vogels, Tim P.; Greenberg, David S.; Macke, Jakob H

doi:10.7554/eLife.56261

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Training deep neural density estimators to identify mechanistic models of neural dynamics

Gonçalves, P. J., Lueckmann, J.-M., Deistler, M., Nonnenmacher, M., Öcal, K., Bassetto, G., et al. (2020). Training deep neural density estimators to identify mechanistic models of neural dynamics. eLife, 9: e56261. doi:10.7554/eLife.56261.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000B-A091-B Version Permalink: https://hdl.handle.net/21.11116/0000-000B-A092-A

Genre: Journal Article

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https://doi.org/10.7554/eLife.56261 (Publisher version) Open Access Gold

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https://doi.org/10.1101/838383 (Preprint) Open Access Green

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Creators:
Gonçalves, Pedro J.¹, Author
Lueckmann, Jan-Matthis¹, Author
Deistler, Michael¹, Author
Nonnenmacher, Marcel¹, Author
Öcal, Kaan¹, Author
Bassetto, Giacomo¹, Author
Chintaluri, Chaitanya¹, Author
Podlaski, William F.¹, Author
Haddad, Sara A.¹, Author
Vogels, Tim P.¹, Author
Greenberg, David S.¹, Author
Macke, Jakob H², Author

Affiliations:
1External Organizations, ou_persistent22
2Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647

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Free keywords: Abt. Schölkopf

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Language(s): eng - English

Dates: Published Online: 2020-09-17

Publication Status: Published online

Pages: 45

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Table of Contents: -

Rev. Type: Peer

Identifiers: DOI: 10.7554/eLife.56261
BibTex Citekey: Goncalvesetal20

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Title: eLife

Source Genre: Journal

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Publ. Info: Cambridge : eLife Sciences Publications

Pages: - Volume / Issue: 9 Sequence Number: e56261 Start / End Page: - Identifier: ISSN: 2050-084X
CoNE: https://pure.mpg.de/cone/journals/resource/2050-084X