Search Results - "Bohté, Sander" :: K.UTB vyhledávací portál | TBU Library Retrieval Portal

Visualizing a joint future of neuroscience and neuromorphic engineering

Visualizing a joint future of neuroscience and neuromorphic engineering

by Zenke, Friedemann, Bohté, Sander M, Clopath, Claudia, Comşa, Iulia M, Göltz, Julian, Maass, Wolfgang, Masquelier, Timothée, Naud, Richard, Neftci, Emre O, Petrovici, Mihai A, Scherr, Franz, Goodman, Dan F M
Published in Neuron (Cambridge, Mass.) (17.02.2021)

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Journal Article

Mechanisms of human dynamic object recognition revealed by sequential deep neural networks

Mechanisms of human dynamic object recognition revealed by sequential deep neural networks

by Sörensen, Lynn K A, Bohté, Sander M, de Jong, Dorina, Slagter, Heleen A, Scholte, H Steven
Published in PLoS computational biology (01.06.2023)

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Journal Article

A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning

A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning

by Mücke, Nikolaj T, Pandey, Prerna, Jain, Shashi, Bohté, Sander M, Oosterlee, Cornelis W
Published in Sensors (Basel, Switzerland) (05.07.2023)

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Journal Article

Accurate online training of dynamical spiking neural networks through Forward Propagation Through Time

Accurate online training of dynamical spiking neural networks through Forward Propagation Through Time

by Yin, Bojian, Corradi, Federico, Bohté, Sander M.
Published in Nature machine intelligence (01.05.2023)

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Journal Article

Arousal state affects perceptual decision-making by modulating hierarchical sensory processing in a large-scale visual system model

Arousal state affects perceptual decision-making by modulating hierarchical sensory processing in a large-scale visual system model

by Sörensen, Lynn K A, Bohté, Sander M, Slagter, Heleen A, Scholte, H Steven
Published in PLoS computational biology (01.04.2022)

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Journal Article

Local minimization of prediction errors drives learning of invariant object representations in a generative network model of visual perception

Local minimization of prediction errors drives learning of invariant object representations in a generative network model of visual perception

by Brucklacher, Matthias, Bohté, Sander M, Mejias, Jorge F, Pennartz, Cyriel M A
Published in Frontiers in computational neuroscience (25.09.2023)

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Journal Article

Leveraging Spiking Deep Neural Networks to Understand the Neural Mechanisms Underlying Selective Attention

Leveraging Spiking Deep Neural Networks to Understand the Neural Mechanisms Underlying Selective Attention

by Sörensen, Lynn K. A, Zambrano, Davide, Slagter, Heleen A, Bohté, Sander M, Scholte, H. Steven
Published in Journal of cognitive neuroscience (05.03.2022)

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Journal Article

Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks

Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks

by Yin, Bojian, Corradi, Federico, Bohté, Sander M.
Published in Nature machine intelligence (01.10.2021)

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Journal Article

Editorial: Artificial Neural Networks as Models of Neural Information Processing

Editorial: Artificial Neural Networks as Models of Neural Information Processing

by van Gerven, Marcel, Bohte, Sander
Published in Frontiers in computational neuroscience (19.12.2017)

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Journal Article

A Taxonomy of Recurrent Learning Rules

A Taxonomy of Recurrent Learning Rules

by Martín-Sánchez, Guillermo, Sander Bohté, Otte, Sebastian
Published in arXiv.org (08.10.2024)

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Paper Journal Article

The deep latent space particle filter for real-time data assimilation with uncertainty quantification

The deep latent space particle filter for real-time data assimilation with uncertainty quantification

by Mücke, Nikolaj T., Bohté, Sander M., Oosterlee, Cornelis W.
Published in Scientific reports (21.08.2024)

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Journal Article

Recurrent neural networks that learn multi-step visual routines with reinforcement learning

Recurrent neural networks that learn multi-step visual routines with reinforcement learning

by Mollard, Sami, Wacongne, Catherine, Bohte, Sander M, Roelfsema, Pieter R
Published in PLoS computational biology (01.04.2024)

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Journal Article

Pricing options and computing implied volatilities using neural networks

Pricing options and computing implied volatilities using neural networks

by Liu, Shuaiqiang, Oosterlee, Cornelis Willebrordus, Bohte, Sander M
Published in Risks (Basel) (09.02.2019)

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Journal Article

How attention can create synaptic tags for the learning of working memories in sequential tasks

How attention can create synaptic tags for the learning of working memories in sequential tasks

by Rombouts, Jaldert O, Bohte, Sander M, Roelfsema, Pieter R
Published in PLoS computational biology (01.03.2015)

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Journal Article

Depth in convolutional neural networks solves scene segmentation

Depth in convolutional neural networks solves scene segmentation

by Seijdel, Noor, Tsakmakidis, Nikos, de Haan, Edward H. F, Bohte, Sander M, Scholte, H. Steven, Gershman, Samuel J, Isik, Leyla
Published in PLoS computational biology (01.07.2020)

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Journal Article

Sparse Computation in Adaptive Spiking Neural Networks

Sparse Computation in Adaptive Spiking Neural Networks

by Zambrano, Davide, Nusselder, Roeland, Scholte, H Steven, Bohté, Sander M
Published in Frontiers in neuroscience (08.01.2019)

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Journal Article

Using the structure of genome data in the design of deep neural networks for predicting amyotrophic lateral sclerosis from genotype

Using the structure of genome data in the design of deep neural networks for predicting amyotrophic lateral sclerosis from genotype

by Yin, Bojian, Balvert, Marleen, van der Spek, Rick A A, Dutilh, Bas E, Bohté, Sander, Veldink, Jan, Schönhuth, Alexander
Published in Bioinformatics (15.07.2019)

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Journal Article

Markov chain generative adversarial neural networks for solving Bayesian inverse problems in physics applications

Markov chain generative adversarial neural networks for solving Bayesian inverse problems in physics applications

by Mücke, Nikolaj T., Sanderse, Benjamin, Bohté, Sander M., Oosterlee, Cornelis W.
Published in Computers & mathematics with applications (1987) (01.10.2023)

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Journal Article

Flexible Working Memory Through Selective Gating and Attentional Tagging

Flexible Working Memory Through Selective Gating and Attentional Tagging

by Kruijne, Wouter, Bohte, Sander M., Roelfsema, Pieter R., Olivers, Christian N. L.
Published in Neural computation (01.01.2021)

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Journal Article

Reduced order modeling for parameterized time-dependent PDEs using spatially and memory aware deep learning

Reduced order modeling for parameterized time-dependent PDEs using spatially and memory aware deep learning

by Mücke, Nikolaj T., Bohté, Sander M., Oosterlee, Cornelis W.
Published in Journal of computational science (01.07.2021)

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