Sander M. Bohté

According to our database, Sander M. Bohté authored at least 88 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

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

Sami Mollard, Catherine Wacongne, Sander M. Bohté, Pieter R. Roelfsema

PLoS Comput. Biol., 2024

Predictive coding with spiking neurons and feedforward gist signaling.

Kwangjun Lee, Shirin Dora, Jorge F. Mejías, Sander M. Bohté, Cyriel M. A. Pennartz

Frontiers Comput. Neurosci., 2024

DPSNN: Spiking Neural Network for Low-Latency Streaming Speech Enhancement.

Tao Sun, Sander M. Bohté

CoRR, 2024

The Deep Latent Space Particle Filter for Real-Time Data Assimilation with Uncertainty Quantification.

Nikolaj Takata Mücke, Sander M. Bohté, Cornelis W. Oosterlee

CoRR, 2024

Understanding the Convergence in Balanced Resonate-and-Fire Neurons.

Saya Higuchi, Sander M. Bohté, Sebastian Otte

CoRR, 2024

Balanced Resonate-and-Fire Neurons.

Saya Higuchi, Sebastian Kairat, Sander M. Bohté, Sebastian Otte

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Masked Image Modeling as a Framework for Self-Supervised Learning Across Eye Movements.

Robin Weiler, Matthias Brucklacher, Cyriel M. A. Pennartz, Sander M. Bohté

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

2023

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

Nikolaj Takata Mücke, Benjamin Sanderse, Sander M. Bohté, Cornelis W. Oosterlee

Comput. Math. Appl., October, 2023

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

Nikolaj Takata Mücke, Prerna Pandey, Shashi Jain, Sander M. Bohté, Cornelis W. Oosterlee

Sensors, July, 2023

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

Bojian Yin, Federico Corradi, Sander M. Bohté

Nat. Mac. Intell., May, 2023

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

Matthias Brucklacher, Sander M. Bohté, Jorge F. Mejías, Cyriel M. A. Pennartz

Frontiers Comput. Neurosci., February, 2023

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

Lynn K. A. Sörensen, Sander M. Bohté, Dorina De Jong, Heleen A. Slagter, H. Steven Scholte

PLoS Comput. Biol., 2023

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking.

Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander M. Bohté, Younes Bouhadjar, Sonia M. Buckley, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Reddy Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve B. Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos P. Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayça Özcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Pao-Sheng Sun, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine D. Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Michael Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi

CoRR, 2023

Efficient Uncertainty Estimation in Spiking Neural Networks via MC-dropout.

Tao Sun, Bojian Yin, Sander M. Bohté

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

2022

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

Lynn K. A. Sörensen, Sander M. Bohté, Heleen A. Slagter, H. Steven Scholte

PLoS Comput. Biol., 2022

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

Lynn K. A. Sörensen, Davide Zambrano, Heleen A. Slagter, Sander M. Bohté, H. Steven Scholte

J. Cogn. Neurosci., 2022

Real-time classification of LIDAR data using discrete-time Recurrent Spiking Neural Networks.

Anca-Diana Vicol, Bojian Yin, Sander M. Bohté

Proceedings of the International Joint Conference on Neural Networks, 2022

Attentive Decision-making and Dynamic Resetting of Continual Running SRNNs for End-to-End Streaming Keyword Spotting.

Bojian Yin, Qinghai Guo, Federico Corradi, Sander M. Bohté

Proceedings of the ICONS 2022: International Conference on Neuromorphic Systems, Knoxville, TN, USA, July 27, 2022

A Taxonomy of Recurrent Learning Rules.

Guillermo Martín-Sánchez, Sander M. Bohté, Sebastian Otte

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

2021

Flexible Working Memory Through Selective Gating and Attentional Tagging.

Wouter Kruijne, Sander M. Bohté, Pieter R. Roelfsema, Christian N. L. Olivers

Neural Comput., 2021

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

Bojian Yin, Federico Corradi, Sander M. Bohté

Nat. Mach. Intell., 2021

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

Nikolaj Takata Mücke, Sander M. Bohté, Cornelis W. Oosterlee

J. Comput. Sci., 2021

Learning continuous-time working memory tasks with on-policy neural reinforcement learning.

Davide Zambrano, Pieter R. Roelfsema, Sander M. Bohté

Neurocomputing, 2021

Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding.

Martin J. Pearson, Shirin Dora, Oliver Struckmeier, Thomas C. Knowles, Ben Mitchinson, Kshitij Tiwari, Ville Kyrki, Sander M. Bohté, Cyriel M. A. Pennartz

Frontiers Robotics AI, 2021

Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical Hierarchy.

Shirin Dora, Sander M. Bohté, Cyriel M. A. Pennartz

Frontiers Comput. Neurosci., 2021

Effective and Efficient Spiking Recurrent Neural Networks.

Bojian Yin, Federico Corradi, Sander M. Bohté

ERCIM News, 2021

LocalNorm: Robust Image Classification Through Dynamically Regularized Normalization.

Bojian Yin, H. Steven Scholte, Sander M. Bohté

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2020

Evolved Neuromorphic Control for High Speed Divergence-Based Landings of MAVs.

Jesse J. Hagenaars, Federico Paredes-Vallés, Sander M. Bohté, Guido C. H. E. de Croon

IEEE Robotics Autom. Lett., 2020

Depth in convolutional neural networks solves scene segmentation.

Noor Seijdel, Nikos Tsakmakidis, Edward H. F. de Haan, Sander M. Bohté, H. Steven Scholte

PLoS Comput. Biol., 2020

Attention-Gated Brain Propagation: How the brain can implement reward-based error backpropagation.

Isabella Pozzi, Sander M. Bohté, Pieter R. Roelfsema

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Effective and Efficient Computation with Multiple-timescale Spiking Recurrent Neural Networks.

Bojian Yin, Federico Corradi, Sander M. Bohté

Proceedings of the International Conference on Neuromorphic Systems, 2020

2019

Generalization in fully-connected neural networks for time series forecasting.

Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohté

J. Comput. Sci., 2019

MuPNet: Multi-modal Predictive Coding Network for Place Recognition by Unsupervised Learning of Joint Visuo-Tactile Latent Representations.

Oliver Struckmeier, Kshitij Tiwari, Shirin Dora, Martin J. Pearson, Sander M. Bohté, Cyriel M. A. Pennartz, Ville Kyrki

CoRR, 2019

LocalNorm: Robust Image Classification through Dynamically Regularized Normalization.

Bojian Yin, Siebren Schaafsma, Henk Corporaal, H. Steven Scholte, Sander M. Bohté

CoRR, 2019

Generalisation in fully-connected neural networks for time series forecasting.

Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohté

CoRR, 2019

Pricing options and computing implied volatilities using neural networks.

Shuaiqiang Liu, Cornelis W. Oosterlee, Sander M. Bohté

CoRR, 2019

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

Bojian Yin, Marleen Balvert, Rick A. A. van der Spek, Bas E. Dutilh, Sander M. Bohté, Jan Veldink, Alexander Schönhuth

Bioinform., 2019

2018

A Biologically Plausible Learning Rule for Deep Learning in the Brain.

Isabella Pozzi, Sander M. Bohté, Pieter R. Roelfsema

CoRR, 2018

On the data-driven COS method.

Álvaro Leitao, Cornelis W. Oosterlee, Luis Ortiz-Gracia, Sander M. Bohté

Appl. Math. Comput., 2018

An image representation based convolutional network for DNA classification.

Bojian Yin, Marleen Balvert, Davide Zambrano, Alexander Schönhuth, Sander M. Bohté

Proceedings of the 6th International Conference on Learning Representations, 2018

Gating Sensory Noise in a Spiking Subtractive LSTM.

Isabella Pozzi, Roeland Nusselder, Davide Zambrano, Sander M. Bohté

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Continuous-Time Spike-Based Reinforcement Learning for Working Memory Tasks.

Marios Karamanis, Davide Zambrano, Sander M. Bohté

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

A Deep Predictive Coding Network for Inferring Hierarchical Causes Underlying Sensory Inputs.

Shirin Dora, Cyriel M. A. Pennartz, Sander M. Bohté

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

2017

Editorial: Artificial Neural Networks as Models of Neural Information Processing.

Marcel van Gerven, Sander M. Bohté

Frontiers Comput. Neurosci., 2017

Efficient Computation in Adaptive Artificial Spiking Neural Networks.

Davide Zambrano, Roeland Nusselder, H. Steven Scholte, Sander M. Bohté

CoRR, 2017

2016

Modern Machine Learning: More with Less, Cheaper and Better.

Sander M. Bohté, Hung Son Nguyen

ERCIM News, 2016

Fast and Efficient Asynchronous Neural Computation with Adapting Spiking Neural Networks.

Davide Zambrano, Sander M. Bohté

CoRR, 2016

Efficient forward propagation of time-sequences in convolutional neural networks using Deep Shifting.

Koen Groenland, Sander M. Bohté

CoRR, 2016

2015

How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks.

Jaldert O. Rombouts, Sander M. Bohté, Pieter R. Roelfsema

PLoS Comput. Biol., 2015

Continuous-time on-policy neural Reinforcement Learning of working memory tasks.

Davide Zambrano, Pieter R. Roelfsema, Sander M. Bohté

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014

Spiking AGREL.

Davide Zambrano, Jaldert O. Rombouts, Cecilia Laschi, Sander M. Bohté

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Learning resets of neural working memory.

Jaldert O. Rombouts, Pieter R. Roelfsema, Sander M. Bohté

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Spiking Neural Networks: Principles and Challenges.

André Grüning, Sander M. Bohté

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2012

Computing with Spiking Neuron Networks.

Hélène Paugam-Moisy, Sander M. Bohté

Proceedings of the Handbook of Natural Computing, 2012

Learning to Recall.

Jaldert O. Rombouts, Pieter R. Roelfsema, Sander M. Bohté

ERCIM News, 2012

Neurally Plausible Reinforcement Learning of Working Memory Tasks.

Jaldert O. Rombouts, Sander M. Bohté, Pieter R. Roelfsema

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model.

Sander M. Bohté

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Biologically Plausible Multi-dimensional Reinforcement Learning in Neural Networks.

Jaldert O. Rombouts, Arjen van Ooyen, Pieter R. Roelfsema, Sander M. Bohté

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

2011

Error-Backpropagation in Networks of Fractionally Predictive Spiking Neurons.

Sander M. Bohté

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2010

Fractionally Predictive Spiking Neurons.

Sander M. Bohté, Jaldert O. Rombouts

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

Adaptive resource allocation for efficient patient scheduling.

Ivan B. Vermeulen, Sander M. Bohté, Sylvia G. Elkhuizen, Han Lameris, Piet J. M. Bakker, Han La Poutré

Artif. Intell. Medicine, 2009

Optimization of Online Patient Scheduling with Urgencies and Preferences.

Ivan B. Vermeulen, Sander M. Bohté, Peter A. N. Bosman, Sylvia G. Elkhuizen, Piet J. M. Bakker, Johannes A. La Poutré

Proceedings of the Artificial Intelligence in Medicine, 2009

The Complex Dynamics of Sponsored Search Markets.

Valentin Robu, Han La Poutré, Sander M. Bohté

Proceedings of the Agents and Data Mining Interaction, 4th International Workshop, 2009

2008

Decentralized Online Scheduling of Combination-Appointments in Hospitals.

Ivan B. Vermeulen, Sander M. Bohté, Sylvia G. Elkhuizen, Piet J. M. Bakker, Han La Poutré

Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling, 2008

2007

Multi-agent Pareto appointment exchanging in hospital patient scheduling.

Ivan B. Vermeulen, Sander M. Bohté, Koye Somefun, Johannes A. La Poutré

Serv. Oriented Comput. Appl., 2007

Reducing the Variability of Neural Responses: A Computational Theory of Spike-Timing-Dependent Plasticity.

Sander M. Bohté, Michael C. Mozer

Neural Comput., 2007

Adaptive Patient Scheduling with Dynamic Resource Usage.

Ivan B. Vermeulen, Sander M. Bohté, Han La Poutré

ERCIM News, 2007

Adaptive Optimization of Hospital Resource Calendars.

Ivan B. Vermeulen, Sander M. Bohté, Sylvia G. Elkhuizen, J. S. Lameris, Piet J. M. Bakker, Johannes A. La Poutré

Proceedings of the Artificial Intelligence in Medicine, 2007

2006

Improving Patient Activity Schedules by Multi-agent Pareto Appointment Exchanging.

Ivan B. Vermeulen, Sander M. Bohté, D. J. A. Somefun, Han La Poutré

Proceedings of the Eighth IEEE International Conference on E-Commerce Technology (CEC 2006) / Third IEEE International Conference on Enterprise Computing, 2006

Strategic Foresighted Learning in Competitive Multi-Agent Games.

Pieter Jan't Hoen, Sander M. Bohté, Han La Poutré

Proceedings of the ECAI 2006, 17th European Conference on Artificial Intelligence, August 29, 2006

Learning from induced changes in opponent (re)actions in multi-agent games.

Pieter Jan't Hoen, Sander M. Bohté, Johannes A. La Poutré

Proceedings of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), 2006

2005

Applications of spiking neural networks.

Sander M. Bohté, Joost N. Kok

Inf. Process. Lett., 2005

Action-Reaction in Multi-Agent Games.

Pieter Jan't Hoen, Sander M. Bohté, Johannes A. La Poutré

Proceedings of the EUMAS 2005, 2005

2004

Market-based recommendation: Agents that compete for consumer attention.

Sander M. Bohté, Enrico H. Gerding, Johannes A. La Poutré

ACM Trans. Internet Techn., 2004

Introduction.

Sander M. Bohté, Michiel C. van Wezel, Joost N. Kok

Nat. Comput., 2004

The evidence for neural information processing with precise spike-times: A survey.

Sander M. Bohté

Nat. Comput., 2004

Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity.

Sander M. Bohté, Michael C. Mozer

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Nonparametric classification with polynomial MPMC cascades.

Sander M. Bohté, Markus Breitenbach, Gregory Z. Grudic

Proceedings of the Machine Learning, 2004

2003

COllective INtelligence with Sequences of Actions - Coordinating Actions in Multi-agent Systems.

Pieter Jan't Hoen, Sander M. Bohté

Proceedings of the Machine Learning: ECML 2003, 2003

Automated Negotiation and Bundling of Information Goods.

D. J. A. Somefun, Enrico H. Gerding, Sander M. Bohté, Johannes A. La Poutré

Proceedings of the Agent-Mediated Electronic Commerce V, 2003

2002

Unsupervised clustering with spiking neurons by sparse temporal coding and multilayer RBF networks.

Sander M. Bohté, Han La Poutré, Joost N. Kok

IEEE Trans. Neural Networks, 2002

Error-backpropagation in temporally encoded networks of spiking neurons.

Sander M. Bohté, Joost N. Kok, Johannes A. La Poutré

Neurocomputing, 2002

Modeling efficient conjunction detection with spiking neural networks.

Sander M. Bohté, Joost N. Kok, Johannes A. La Poutré

Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

An Extensible Agent Architecture for a Competitive Market-Based Allocation of Consumer Attention Space.

Pieter Jan't Hoen, Sander M. Bohté, Enrico H. Gerding, Johannes A. La Poutré

Proceedings of the Agent-Mediated Electronic Commerce IV, 2002

2001

Competitive market-based allocation of consumer attention space.

Sander M. Bohté, Enrico H. Gerding, Johannes A. La Poutré

Proceedings of the Proceedings 3rd ACM Conference on Electronic Commerce (EC-2001), 2001

2000

The Effects of Pair-wise and Higher-order Correlations on the Firing Rate of a Postsynaptic Neuron.

Sander M. Bohté, Henk Spekreijse, Pieter R. Roelfsema

Neural Comput., 2000

Unsupervised Classification of Complex Clusters in Networks of Spiking Neurons.

Sander M. Bohté, Johannes A. La Poutré, Joost N. Kok

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

SpikeProp: backpropagation for networks of spiking neurons.

Sander M. Bohté, Joost N. Kok, Johannes A. La Poutré

Proceedings of the 8th European Symposium on Artificial Neural Networks, 2000