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Sander M Bohte

Showing results (1-10 of 11) with videos related to

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Neural Computation|January 9, 2007
Reducing the variability of neural responses: a computational theory of spike-timing-dependent plasticitySander M Bohte, Michael C Mozer
Plos Computational Biology|April 15, 2026
How the visual brain can learn to parse images using a multiscale, incremental grouping processSami Mollard, Sander M Bohte, Pieter R Roelfsema
Frontiers in Computational Neuroscience|August 16, 2021
Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical HierarchyShirin Dora, Sander M Bohte, Cyriel M A Pennartz
Plos Computational Biology|March 6, 2015
How attention can create synaptic tags for the learning of working memories in sequential tasksJaldert O Rombouts, Sander M Bohte, Pieter R Roelfsema
Plos One|December 31, 2024
Biologically plausible gated recurrent neural networks for working memory and learning-to-learnAlexandra R van den Berg, Pieter R Roelfsema, Sander M Bohte
Plos Computational Biology|April 29, 2024
Recurrent neural networks that learn multi-step visual routines with reinforcement learningSami Mollard, Catherine Wacongne, Sander M Bohte, et al.
Neural Computation|October 20, 2020
Flexible Working Memory Through Selective Gating and Attentional TaggingWouter Kruijne, Sander M Bohte, Pieter R Roelfsema, et al.
Frontiers in Computational Neuroscience|April 29, 2024
Predictive coding with spiking neurons and feedforward gist signalingKwangjun Lee, Shirin Dora, Jorge F Mejias, et al.
Cortex; a Journal Devoted to the Study of the Nervous System and Behavior|November 19, 2017
Visual pathways from the perspective of cost functions and multi-task deep neural networksH Steven Scholte, Max M Losch, Kandan Ramakrishnan, et al.
Plos Computational Biology|July 25, 2020
Depth in convolutional neural networks solves scene segmentationNoor Seijdel, Nikos Tsakmakidis, Edward H F de Haan, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Neural Computation|January 9, 2007
Reducing the variability of neural responses: a computational theory of spike-timing-dependent plasticitySander M Bohte, Michael C Mozer
Plos Computational Biology|April 15, 2026
How the visual brain can learn to parse images using a multiscale, incremental grouping processSami Mollard, Sander M Bohte, Pieter R Roelfsema
Frontiers in Computational Neuroscience|August 16, 2021
Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical HierarchyShirin Dora, Sander M Bohte, Cyriel M A Pennartz
Plos Computational Biology|March 6, 2015
How attention can create synaptic tags for the learning of working memories in sequential tasksJaldert O Rombouts, Sander M Bohte, Pieter R Roelfsema
Plos One|December 31, 2024
Biologically plausible gated recurrent neural networks for working memory and learning-to-learnAlexandra R van den Berg, Pieter R Roelfsema, Sander M Bohte
Plos Computational Biology|April 29, 2024
Recurrent neural networks that learn multi-step visual routines with reinforcement learningSami Mollard, Catherine Wacongne, Sander M Bohte, et al.
Neural Computation|October 20, 2020
Flexible Working Memory Through Selective Gating and Attentional TaggingWouter Kruijne, Sander M Bohte, Pieter R Roelfsema, et al.
Frontiers in Computational Neuroscience|April 29, 2024
Predictive coding with spiking neurons and feedforward gist signalingKwangjun Lee, Shirin Dora, Jorge F Mejias, et al.
Cortex; a Journal Devoted to the Study of the Nervous System and Behavior|November 19, 2017
Visual pathways from the perspective of cost functions and multi-task deep neural networksH Steven Scholte, Max M Losch, Kandan Ramakrishnan, et al.
Plos Computational Biology|July 25, 2020
Depth in convolutional neural networks solves scene segmentationNoor Seijdel, Nikos Tsakmakidis, Edward H F de Haan, et al.
Pageof 2