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Martin Schrimpf

Showing results (1-10 of 9) with videos related to

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Neurobiology of Language (Cambridge, Mass.)|April 22, 2024
Artificial Neural Network Language Models Predict Human Brain Responses to Language Even After a Developmentally Realistic Amount of TrainingEghbal A Hosseini, Martin Schrimpf, Yian Zhang, et al.
Biorxiv : the Preprint Server for Biology|April 24, 2023
Driving and suppressing the human language network using large language modelsGreta Tuckute, Aalok Sathe, Shashank Srikant, et al.
Neuron|September 12, 2020
Integrative Benchmarking to Advance Neurally Mechanistic Models of Human IntelligenceMartin Schrimpf, Jonas Kubilius, Michael J Lee, et al.
Nature Human Behaviour|January 3, 2024
Driving and suppressing the human language network using large language modelsGreta Tuckute, Aalok Sathe, Shashank Srikant, et al.
Proceedings of the National Academy of Sciences of the United States of America|January 12, 2021
Unsupervised neural network models of the ventral visual streamChengxu Zhuang, Siming Yan, Aran Nayebi, et al.
The Behavioral and Brain Sciences|February 2, 2024
Let's move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human vision - CORRIGENDUMJames J DiCarlo, Daniel L K Yamins, Michael E Ferguson, et al.
The Behavioral and Brain Sciences|December 6, 2023
Let's move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human visionJames J DiCarlo, Daniel L K Yamins, Michael E Ferguson, et al.
Proceedings of the National Academy of Sciences of the United States of America|November 5, 2021
The neural architecture of language: Integrative modeling converges on predictive processingMartin Schrimpf, Idan Asher Blank, Greta Tuckute, et al.
Proceedings of the National Academy of Sciences of the United States of America|August 15, 2018
Recurrent computations for visual pattern completionHanlin Tang, Martin Schrimpf, William Lotter, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Neurobiology of Language (Cambridge, Mass.)|April 22, 2024
Artificial Neural Network Language Models Predict Human Brain Responses to Language Even After a Developmentally Realistic Amount of TrainingEghbal A Hosseini, Martin Schrimpf, Yian Zhang, et al.
Biorxiv : the Preprint Server for Biology|April 24, 2023
Driving and suppressing the human language network using large language modelsGreta Tuckute, Aalok Sathe, Shashank Srikant, et al.
Neuron|September 12, 2020
Integrative Benchmarking to Advance Neurally Mechanistic Models of Human IntelligenceMartin Schrimpf, Jonas Kubilius, Michael J Lee, et al.
Nature Human Behaviour|January 3, 2024
Driving and suppressing the human language network using large language modelsGreta Tuckute, Aalok Sathe, Shashank Srikant, et al.
Proceedings of the National Academy of Sciences of the United States of America|January 12, 2021
Unsupervised neural network models of the ventral visual streamChengxu Zhuang, Siming Yan, Aran Nayebi, et al.
The Behavioral and Brain Sciences|February 2, 2024
Let's move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human vision - CORRIGENDUMJames J DiCarlo, Daniel L K Yamins, Michael E Ferguson, et al.
The Behavioral and Brain Sciences|December 6, 2023
Let's move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human visionJames J DiCarlo, Daniel L K Yamins, Michael E Ferguson, et al.
Proceedings of the National Academy of Sciences of the United States of America|November 5, 2021
The neural architecture of language: Integrative modeling converges on predictive processingMartin Schrimpf, Idan Asher Blank, Greta Tuckute, et al.
Proceedings of the National Academy of Sciences of the United States of America|August 15, 2018
Recurrent computations for visual pattern completionHanlin Tang, Martin Schrimpf, William Lotter, et al.
Pageof 1