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Thomas Serre

Showing results (11-20 of 50) with videos related to

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Trends in Cognitive Sciences|December 24, 2025
Better artificial intelligence does not mean better models of biologyDrew Linsley, Pinyuan Feng, Thomas Serre
Interface Focus|June 29, 2018
Not-So-CLEVR: learning same-different relations strains feedforward neural networksJunkyung Kim, Matthew Ricci, Thomas Serre
Plos Computational Biology|September 4, 2015
Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual CategorizationImri Sofer, Sébastien M Crouzet, Thomas Serre
Psychological Review|September 21, 2018
Complementary surrounds explain diverse contextual phenomena across visual modalitiesDavid A Mély, Drew Linsley, Thomas Serre
American Journal of Botany|March 23, 2022
Decoding family-level features for modern and fossil leaves from computer-vision heat mapsEdward J Spagnuolo, Peter Wilf, Thomas Serre
Vision Research|May 25, 2010
What and where: a Bayesian inference theory of attentionSharat Chikkerur, Thomas Serre, Cheston Tan, et al.
Advances in Neural Information Processing Systems|October 3, 2023
What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability MethodsJulien Colin, Thomas Fel, Rémi Cadène, et al.
Arxiv|August 13, 2025
Enhancing deep neural networks through complex-valued representations and Kuramoto synchronization dynamicsSabine Muzellec, Andrea Alamia, Thomas Serre, et al.
Advances in Neural Information Processing Systems|July 19, 2023
Harmonizing the object recognition strategies of deep neural networks with humansThomas Fel, Ivan Felipe, Drew Linsley, et al.
Neuroimage|October 20, 2015
Fast ventral stream neural activity enables rapid visual categorizationMaxime Cauchoix, Sébastien M Crouzet, Denis Fize, et al.
Pageof 5

Showing results (11-20 of 50) with videos related to

Sort By:
Pageof 5
Trends in Cognitive Sciences|December 24, 2025
Better artificial intelligence does not mean better models of biologyDrew Linsley, Pinyuan Feng, Thomas Serre
Interface Focus|June 29, 2018
Not-So-CLEVR: learning same-different relations strains feedforward neural networksJunkyung Kim, Matthew Ricci, Thomas Serre
Plos Computational Biology|September 4, 2015
Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual CategorizationImri Sofer, Sébastien M Crouzet, Thomas Serre
Psychological Review|September 21, 2018
Complementary surrounds explain diverse contextual phenomena across visual modalitiesDavid A Mély, Drew Linsley, Thomas Serre
American Journal of Botany|March 23, 2022
Decoding family-level features for modern and fossil leaves from computer-vision heat mapsEdward J Spagnuolo, Peter Wilf, Thomas Serre
Vision Research|May 25, 2010
What and where: a Bayesian inference theory of attentionSharat Chikkerur, Thomas Serre, Cheston Tan, et al.
Advances in Neural Information Processing Systems|October 3, 2023
What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability MethodsJulien Colin, Thomas Fel, Rémi Cadène, et al.
Arxiv|August 13, 2025
Enhancing deep neural networks through complex-valued representations and Kuramoto synchronization dynamicsSabine Muzellec, Andrea Alamia, Thomas Serre, et al.
Advances in Neural Information Processing Systems|July 19, 2023
Harmonizing the object recognition strategies of deep neural networks with humansThomas Fel, Ivan Felipe, Drew Linsley, et al.
Neuroimage|October 20, 2015
Fast ventral stream neural activity enables rapid visual categorizationMaxime Cauchoix, Sébastien M Crouzet, Denis Fize, et al.
Pageof 5