Prof. dr. S.M. (Sander) Bohte
Faculty of Science
Swammerdam Institute for Life Sciences
Visiting address
- Science Park 904
Postal address
- Postbus 94246
1090 GE Amsterdam
Contact details
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Publications
2021
Dora, S., Bohte, S. M., & Pennartz, C. M. A. (2021). Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical Hierarchy. Frontiers in Computational Neuroscience, 15, [666131]. https://doi.org/10.3389/fncom.2021.666131 [details]- Pearson, M. J., Dora, S., Struckmeier, O., Knowles, T. C., Mitchinson, B., Tiwari, K., Kyrki, V., Bohte, S., & Pennartz, C. M. A. (2021). Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding. Frontiers in Robotics and AI, 8, 732023. https://doi.org/10.3389/frobt.2021.732023
- Yin, B., Scholte, H. S., & Bohté, S. (2021). LocalNorm: Robust Image Classification Through Dynamically Regularized Normalization. In I. Farkaš, P. Masulli, S. Otte, & S. Wermter (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2021: 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14–17, 2021 : proceedings (Vol. IV, pp. 240-252). (Lecture Notes in Computer Science; Vol. 12894). Springer. https://doi.org/10.1007/978-3-030-86380-7_20 [details]
2020
- Seijdel, N., Tsakmakidis, N., de Haan, E. H. F., Bohte, S. M., & Scholte, H. S. (2020). Depth in convolutional neural networks solves scene segmentation. PLoS Computational Biology, 16(7), [e1008022]. https://doi.org/10.1371/journal.pcbi.1008022 [details]
2019
- Zambrano, D., Nusselder, R., Scholte, H. S., & Bohté, S. M. (2019). Sparse Computation in Adaptive Spiking Neural Networks. Frontiers in Neuroscience, 12, [987]. https://doi.org/10.3389/fnins.2018.00987 [details]
2018
- Scholte, H. S., Losch, M. M., Ramakrishnan, K., de Haan, E. H. F., & Bohte, S. M. (2018). Visual pathways from the perspective of cost functions and multi-task deep neural networks. Cortex, 98, 249-261. https://doi.org/10.1016/j.cortex.2017.09.019 [details]
2012
- Bohte, S. M., Scholte, H. S., & Ghebreab, S. (2012). Information-Maximizing Local Spatial Scale Selection in Early Visual Processing. Abstract from NIPS Workshop on Information in Perception and Action, Lake Tahoe, December 2012, . http://www.montefiore.ulg.ac.be/~tjung/nips12workshop
2019
- Seijdel, N., Tsakmakidis, N., De Haan, E. H. F., Bohte, S. M., & Scholte, H. S. (2019). Depth in convolutional neural networks solves scene segmentation. (Version 1 ed.) BioRxiv. https://doi.org/10.1101/2019.12.16.877753 [details]
2020
- Sörensen, L. K. A., Zambrano, D., Slagter, H., Bohte, S. & Scholte, S. (16-12-2020). ModelAnalysis. Universiteit van Amsterdam. https://doi.org/10.21942/uva.13386377.v1
- Sörensen, L. K. A., Zambrano, D., Slagter, H., Bohte, S. & Scholte, S. (16-12-2020). ModelTraining. Universiteit van Amsterdam. https://doi.org/10.21942/uva.13386395.v1
- Sörensen, L. K. A., Zambrano, D., Slagter, H., Bohte, S. & Scholte, S. (16-12-2020). ModelEvaluation. Universiteit van Amsterdam. https://doi.org/10.21942/uva.13385471.v1
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Ancillary activities
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Deep Blue Capital NV
Adviseur -
CWI
Senior onderzoeker
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Deep Blue Capital NV
Dora, S., Bohte, S. M., & Pennartz, C. M. A. (2021). Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical Hierarchy. Frontiers in Computational Neuroscience, 15, [666131].