Sander M. Bohté

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 53

Top Topics

Online Training

Biologically Plausible

Top Venues

PLoS Comput. Biol.

Frontiers Comput. Neurosci.

Publications

Saya Higuchi, Sander M. Bohté, Sebastian Otte
Understanding the Convergence in Balanced Resonate-and-Fire Neurons. CoRR (2024)
Nikolaj Takata Mücke, Sander M. Bohté, Cornelis W. Oosterlee
The Deep Latent Space Particle Filter for Real-Time Data Assimilation with Uncertainty Quantification. CoRR (2024)
Robin Weiler, Matthias Brucklacher, Cyriel M. A. Pennartz, Sander M. Bohté
Masked Image Modeling as a Framework for Self-Supervised Learning across Eye Movements. CoRR (2024)
Saya Higuchi, Sebastian Kairat, Sander M. Bohté, Sebastian Otte
Balanced Resonate-and-Fire Neurons. CoRR (2024)
Nikolaj Takata Mücke, Benjamin Sanderse, Sander M. Bohté, Cornelis W. Oosterlee
Markov chain generative adversarial neural networks for solving Bayesian inverse problems in physics applications. Comput. Math. Appl. 147 (2023)
Lynn K. A. Sörensen, Sander M. Bohté, Dorina De Jong, Heleen A. Slagter, H. Steven Scholte
Mechanisms of human dynamic object recognition revealed by sequential deep neural networks. PLoS Comput. Biol. 19 (6) (2023)
Nikolaj Takata Mücke, Prerna Pandey, Shashi Jain, Sander M. Bohté, Cornelis W. Oosterlee
A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning. Sensors 23 (13) (2023)
Bojian Yin, Federico Corradi, Sander M. Bohté
Accurate online training of dynamical spiking neural networks through Forward Propagation Through Time. Nat. Mac. Intell. 5 (5) (2023)
Matthias Brucklacher, Sander M. Bohté, Jorge F. Mejías, Cyriel M. A. Pennartz
Local minimization of prediction errors drives learning of invariant object representations in a generative network model of visual perception. Frontiers Comput. Neurosci. 17 (2023)
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 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
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. CoRR (2023)
Tao Sun, Bojian Yin, Sander M. Bohté
Efficient Uncertainty Estimation in Spiking Neural Networks via MC-dropout. CoRR (2023)
Bojian Yin, Qinghai Guo, Federico Corradi, Sander M. Bohté
Attentive Decision-making and Dynamic Resetting of Continual Running SRNNs for End-to-End Streaming Keyword Spotting. ICONS (2022)
Anca-Diana Vicol, Bojian Yin, Sander M. Bohté
Real-time classification of LIDAR data using discrete-time Recurrent Spiking Neural Networks. IJCNN (2022)
Lynn K. A. Sörensen, Davide Zambrano, Heleen A. Slagter, Sander M. Bohté, H. Steven Scholte
Leveraging Spiking Deep Neural Networks to Understand the Neural Mechanisms Underlying Selective Attention. J. Cogn. Neurosci. 34 (4) (2022)
Lynn K. A. Sörensen, Sander M. Bohté, Heleen A. Slagter, H. Steven Scholte
Arousal state affects perceptual decision-making by modulating hierarchical sensory processing in a large-scale visual system model. PLoS Comput. Biol. 18 (4) (2022)
Guillermo Martín-Sánchez, Sander M. Bohté, Sebastian Otte
A Taxonomy of Recurrent Learning Rules. ICANN (1) (2022)
Guillermo Martín-Sánchez, Sander M. Bohté, Sebastian Otte
A Taxonomy of Recurrent Learning Rules. CoRR (2022)
Shirin Dora, Sander M. Bohté, Cyriel M. A. Pennartz
Deep Gated Hebbian Predictive Coding Accounts for Emergence of Complex Neural Response Properties Along the Visual Cortical Hierarchy. Frontiers Comput. Neurosci. 15 (2021)
Bojian Yin, Federico Corradi, Sander M. Bohté
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks. CoRR (2021)
Bojian Yin, Federico Corradi, Sander M. Bohté
Accurate online training of dynamical spiking neural networks through Forward Propagation Through Time. CoRR (2021)
Wouter Kruijne, Sander M. Bohté, Pieter R. Roelfsema, Christian N. L. Olivers
Flexible Working Memory Through Selective Gating and Attentional Tagging. Neural Comput. 33 (1) (2021)
Bojian Yin, H. Steven Scholte, Sander M. Bohté
LocalNorm: Robust Image Classification Through Dynamically Regularized Normalization. ICANN (4) (2021)
Martin J. Pearson, Shirin Dora, Oliver Struckmeier, Thomas C. Knowles, Ben Mitchinson, Kshitij Tiwari, Ville Kyrki, Sander M. Bohté, Cyriel M. A. Pennartz
Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding. Frontiers Robotics AI 8 (2021)
Nikolaj Takata Mücke, Sander M. Bohté, Cornelis W. Oosterlee
Reduced order modeling for parameterized time-dependent PDEs using spatially and memory aware deep learning. J. Comput. Sci. 53 (2021)
Bojian Yin, Federico Corradi, Sander M. Bohté
Effective and Efficient Spiking Recurrent Neural Networks. ERCIM News 2021 (125) (2021)
Nikolaj Takata Mücke, Benjamin Sanderse, Sander M. Bohté, Cornelis W. Oosterlee
Markov Chain Generative Adversarial Neural Networks for Solving Bayesian Inverse Problems in Physics Applications. CoRR (2021)
Bojian Yin, Federico Corradi, Sander M. Bohté
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks. Nat. Mach. Intell. 3 (10) (2021)
Davide Zambrano, Pieter R. Roelfsema, Sander M. Bohté
Learning continuous-time working memory tasks with on-policy neural reinforcement learning. Neurocomputing 461 (2021)
Bojian Yin, Federico Corradi, Sander M. Bohté
Effective and Efficient Computation with Multiple-timescale Spiking Recurrent Neural Networks. ICONS (2020)
Noor Seijdel, Nikos Tsakmakidis, Edward H. F. de Haan, Sander M. Bohté, H. Steven Scholte
Depth in convolutional neural networks solves scene segmentation. PLoS Comput. Biol. 16 (7) (2020)
Nikolaj Takata Mücke, Sander M. Bohté, Cornelis W. Oosterlee
Reduced Order Modeling for Parameterized Time-Dependent PDEs using Spatially and Memory Aware Deep Learning. CoRR (2020)
Isabella Pozzi, Sander M. Bohté, Pieter R. Roelfsema
Attention-Gated Brain Propagation: How the brain can implement reward-based error backpropagation. NeurIPS (2020)
Bojian Yin, Federico Corradi, Sander M. Bohté
Effective and Efficient Computation with Multiple-timescale Spiking Recurrent Neural Networks. CoRR (2020)
Jesse J. Hagenaars, Federico Paredes-Vallés, Sander M. Bohté, Guido C. H. E. de Croon
Evolved Neuromorphic Control for High Speed Divergence-Based Landings of MAVs. IEEE Robotics Autom. Lett. 5 (4) (2020)
Jesse J. Hagenaars, Federico Paredes-Vallés, Sander M. Bohté, Guido C. H. E. de Croon
Evolved Neuromorphic Control for High Speed Divergence-based Landings of MAVs. CoRR (2020)
Shuaiqiang Liu, Cornelis W. Oosterlee, Sander M. Bohté
Pricing options and computing implied volatilities using neural networks. CoRR (2019)
Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohté
Generalization in fully-connected neural networks for time series forecasting. J. Comput. Sci. 36 (2019)
Oliver Struckmeier, Kshitij Tiwari, Shirin Dora, Martin J. Pearson, Sander M. Bohté, Cyriel M. A. Pennartz, Ville Kyrki
MuPNet: Multi-modal Predictive Coding Network for Place Recognition by Unsupervised Learning of Joint Visuo-Tactile Latent Representations. CoRR (2019)
Bojian Yin, Siebren Schaafsma, Henk Corporaal, H. Steven Scholte, Sander M. Bohté
LocalNorm: Robust Image Classification through Dynamically Regularized Normalization. CoRR (2019)
Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohté
Generalisation in fully-connected neural networks for time series forecasting. CoRR (2019)
Bojian Yin, Marleen Balvert, Rick A. A. van der Spek, Bas E. Dutilh, Sander M. Bohté, Jan Veldink, Alexander Schönhuth
Using the structure of genome data in the design of deep neural networks for predicting amyotrophic lateral sclerosis from genotype. Bioinform. 35 (14) (2019)
Bojian Yin, Marleen Balvert, Davide Zambrano, Alexander Schönhuth, Sander M. Bohté
An image representation based convolutional network for DNA classification. CoRR (2018)
Marios Karamanis, Davide Zambrano, Sander M. Bohté
Continuous-Time Spike-Based Reinforcement Learning for Working Memory Tasks. ICANN (2) (2018)
Shirin Dora, Cyriel M. A. Pennartz, Sander M. Bohté
A Deep Predictive Coding Network for Inferring Hierarchical Causes Underlying Sensory Inputs. ICANN (3) (2018)
Álvaro Leitao, Cornelis W. Oosterlee, Luis Ortiz-Gracia, Sander M. Bohté
On the data-driven COS method. Appl. Math. Comput. 317 (2018)
Isabella Pozzi, Sander M. Bohté, Pieter R. Roelfsema
A Biologically Plausible Learning Rule for Deep Learning in the Brain. CoRR (2018)
Isabella Pozzi, Roeland Nusselder, Davide Zambrano, Sander M. Bohté
Gating Sensory Noise in a Spiking Subtractive LSTM. ICANN (1) (2018)
Bojian Yin, Marleen Balvert, Davide Zambrano, Alexander Schönhuth, Sander M. Bohté
An image representation based convolutional network for DNA classification. ICLR (Poster) (2018)
Marcel van Gerven, Sander M. Bohté
Editorial: Artificial Neural Networks as Models of Neural Information Processing. Frontiers Comput. Neurosci. 11 (2017)
Davide Zambrano, Roeland Nusselder, H. Steven Scholte, Sander M. Bohté
Efficient Computation in Adaptive Artificial Spiking Neural Networks. CoRR (2017)
Koen Groenland, Sander M. Bohté
Efficient forward propagation of time-sequences in convolutional neural networks using Deep Shifting. CoRR (2016)
Davide Zambrano, Sander M. Bohté
Fast and Efficient Asynchronous Neural Computation with Adapting Spiking Neural Networks. CoRR (2016)
Sander M. Bohté, Hung Son Nguyen
Modern Machine Learning: More with Less, Cheaper and Better. ERCIM News 2016 (107) (2016)
Jaldert O. Rombouts, Sander M. Bohté, Pieter R. Roelfsema
How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks. PLoS Comput. Biol. 11 (3) (2015)
Davide Zambrano, Pieter R. Roelfsema, Sander M. Bohté
Continuous-time on-policy neural Reinforcement Learning of working memory tasks. IJCNN (2015)
Davide Zambrano, Jaldert O. Rombouts, Cecilia Laschi, Sander M. Bohté
Spiking AGREL. ESANN (2014)
André Grüning, Sander M. Bohté
Spiking Neural Networks: Principles and Challenges. ESANN (2014)
Jaldert O. Rombouts, Pieter R. Roelfsema, Sander M. Bohté
Learning resets of neural working memory. ESANN (2014)
Sander M. Bohté
Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model. NIPS (2012)
Jaldert O. Rombouts, Arjen van Ooyen, Pieter R. Roelfsema, Sander M. Bohté
Biologically Plausible Multi-dimensional Reinforcement Learning in Neural Networks. ICANN (1) (2012)
Jaldert O. Rombouts, Pieter R. Roelfsema, Sander M. Bohté
Learning to Recall. ERCIM News 2012 (91) (2012)
Jaldert O. Rombouts, Sander M. Bohté, Pieter R. Roelfsema
Neurally Plausible Reinforcement Learning of Working Memory Tasks. NIPS (2012)
Sander M. Bohté
Error-Backpropagation in Networks of Fractionally Predictive Spiking Neurons. ICANN (1) (2011)
Sander M. Bohté, Jaldert O. Rombouts
Fractionally Predictive Spiking Neurons CoRR (2010)
Sander M. Bohté, Jaldert O. Rombouts
Fractionally Predictive Spiking Neurons. NIPS (2010)
Ivan B. Vermeulen, Sander M. Bohté, Sylvia G. Elkhuizen, Han Lameris, Piet J. M. Bakker, Han La Poutré
Adaptive resource allocation for efficient patient scheduling. Artif. Intell. Medicine 46 (1) (2009)
Valentin Robu, Han La Poutré, Sander M. Bohté
The Complex Dynamics of Sponsored Search Markets. ADMI (2009)
Ivan B. Vermeulen, Sander M. Bohté, Peter A. N. Bosman, Sylvia G. Elkhuizen, Piet J. M. Bakker, Johannes A. La Poutré
Optimization of Online Patient Scheduling with Urgencies and Preferences. AIME (2009)
Ivan B. Vermeulen, Sander M. Bohté, Sylvia G. Elkhuizen, Piet J. M. Bakker, Han La Poutré
Decentralized Online Scheduling of Combination-Appointments in Hospitals. ICAPS (2008)
Ivan B. Vermeulen, Sander M. Bohté, Koye Somefun, Johannes A. La Poutré
Multi-agent Pareto appointment exchanging in hospital patient scheduling. Serv. Oriented Comput. Appl. 1 (3) (2007)
Ivan B. Vermeulen, Sander M. Bohté, Sylvia G. Elkhuizen, J. S. Lameris, Piet J. M. Bakker, Johannes A. La Poutré
Adaptive Optimization of Hospital Resource Calendars. AIME (2007)
Ivan B. Vermeulen, Sander M. Bohté, Han La Poutré
Adaptive Patient Scheduling with Dynamic Resource Usage. ERCIM News 2007 (69) (2007)
Sander M. Bohté, Michael C. Mozer
Reducing the Variability of Neural Responses: A Computational Theory of Spike-Timing-Dependent Plasticity. Neural Comput. 19 (2) (2007)
Pieter Jan't Hoen, Sander M. Bohté, Johannes A. La Poutré
Learning from induced changes in opponent (re)actions in multi-agent games. AAMAS (2006)
Ivan B. Vermeulen, Sander M. Bohté, D. J. A. Somefun, Han La Poutré
Improving Patient Activity Schedules by Multi-agent Pareto Appointment Exchanging. CEC/EEE (2006)
Pieter Jan't Hoen, Sander M. Bohté, Han La Poutré
Strategic Foresighted Learning in Competitive Multi-Agent Games. ECAI (2006)
Sander M. Bohté, Michael C. Mozer
Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity. BNAIC (2005)
Pieter Jan't Hoen, Sander M. Bohté, Johannes A. La Poutré
Action-Reaction in Multi-Agent Games. EUMAS (2005)
Sander M. Bohté, Joost N. Kok
Applications of spiking neural networks. Inf. Process. Lett. 95 (6) (2005)
Sander M. Bohté, Michiel C. van Wezel, Joost N. Kok
Introduction. Nat. Comput. 3 (2) (2004)
Sander M. Bohté, Enrico Gerding, Johannes A. La Poutré
Market-based recommendation: Agents that compete for consumer attention. ACM Trans. Internet Techn. 4 (4) (2004)
Sander M. Bohté, Markus Breitenbach, Gregory Z. Grudic
Nonparametric classification with polynomial MPMC cascades. ICML (2004)
Sander M. Bohté
The evidence for neural information processing with precise spike-times: A survey. Nat. Comput. 3 (2) (2004)
Sander M. Bohté, Michael C. Mozer
Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity. NIPS (2004)
D. J. A. Somefun, Enrico Gerding, Sander M. Bohté, Johannes A. La Poutré
Automated Negotiation and Bundling of Information Goods. AMEC (2003)
Pieter Jan't Hoen, Sander M. Bohté
COllective INtelligence with Sequences of Actions - Coordinating Actions in Multi-agent Systems. ECML (2003)
Sander M. Bohté, Joost N. Kok, Johannes A. La Poutré
Modeling efficient conjunction detection with spiking neural networks. ESANN (2002)
Pieter Jan't Hoen, Sander M. Bohté, Enrico Gerding, Johannes A. La Poutré
An Extensible Agent Architecture for a Competitive Market-Based Allocation of Consumer Attention Space. AMEC (2002)
Sander M. Bohté, Han La Poutré, Joost N. Kok
Unsupervised clustering with spiking neurons by sparse temporal coding and multilayer RBF networks. IEEE Trans. Neural Networks 13 (2) (2002)
Sander M. Bohté, Joost N. Kok, Johannes A. La Poutré
Error-backpropagation in temporally encoded networks of spiking neurons. Neurocomputing 48 (1-4) (2002)
Sander M. Bohté, Enrico Gerding, Johannes A. La Poutré
Competitive market-based allocation of consumer attention space. EC (2001)
Sander M. Bohté, Henk Spekreijse, Pieter R. Roelfsema
The Effects of Pair-wise and Higher-order Correlations on the Firing Rate of a Postsynaptic Neuron. Neural Comput. 12 (1) (2000)
Sander M. Bohté, Johannes A. La Poutré, Joost N. Kok
Unsupervised Classification of Complex Clusters in Networks of Spiking Neurons. IJCNN (3) (2000)
Sander M. Bohté, Joost N. Kok, Johannes A. La Poutré
SpikeProp: backpropagation for networks of spiking neurons. ESANN (2000)