<p>One-vs-others attention: Scalable multimodal learning</p>

Michal Golovanevsky; Eva Schiller; Akira Nair; Eric Han; Ritambhara Singh; Carsten Eickhoff

doi:10.7490/f1000research.1119879.1

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Golovanevsky M, Schiller E, Nair A et al. One-vs-others attention: Scalable multimodal learning [version 1; not peer reviewed]. F1000Research 2024, 13:1109 (poster) (https://doi.org/10.7490/f1000research.1119879.1)

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One-vs-others attention: Scalable multimodal learning

Michal Golovanevsky, Eva Schiller, Akira Nair, Eric Han, Ritambhara Singh¹, Carsten Eickhoff

Published 01 Oct 2024 (https://doi.org/10.7490/f1000research.1119879.1)

Author Affiliations

¹ Computer Science, Brown University Department of Computer Science, Providence, Rhode Island, USA

Copyright © 2024 Golovanevsky M et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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CITE

Published 01 Oct 2024

One-vs-others attention: Scalable multimodal learning
[version 1; not peer reviewed]

Michal Golovanevsky, Eva Schiller, Akira Nair, Eric Han, Ritambhara Singh¹, Carsten Eickhoff

Author Affiliations

¹ Computer Science, Brown University Department of Computer Science, Providence, Rhode Island, USA

Abstract

Competing Interests

No competing interests were disclosed

Keywords

deep learning, multimodal learning, attention, clinical application

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