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ORCIDSander Keemink
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2020 – today
- 2026
[j4]Sigur de Vries
, Sander Keemink, Marcel van Gerven:
Discovering continuous-time memory-based symbolic policies using genetic programming. Genet. Program. Evolvable Mach. 27(1): 5 (2026)- [i8]Sigur de Vries, Sander W. Keemink, Marcel A. J. van Gerven:
Symbolic Discovery of Stochastic Differential Equations with Genetic Programming. CoRR abs/2603.09597 (2026) - [i7]André Urbano, Pablo Lanillos, Sander Keemink:
Efficient and robust control with spikes that constrain free energy. CoRR abs/2603.09729 (2026) - 2025
- [j3]Sander W. Keemink, Mark C. W. van Rossum:
Biases in neural population codes with a few active neurons. PLoS Comput. Biol. 21(4): 1012969 (2025) - [c3]Sigur de Vries, Sander Wessel Keemink, Marcel Antonius Johannes van Gerven:
Kozax: Flexible and Scalable Genetic Programming in JAX. GECCO Companion 2025: 603-606 - [i6]Sigur de Vries, Sander W. Keemink, Marcel A. J. van Gerven:
Kozax: Flexible and Scalable Genetic Programming in JAX. CoRR abs/2502.03047 (2025) - [i5]Paolo Agliati, André Urbano, Pablo Lanillos, Nasir Ahmad, Marcel van Gerven, Sander W. Keemink:
Spiking neurons as predictive controllers of linear systems. CoRR abs/2507.16495 (2025) - 2024
- [j2]Filip S. Slijkhuis, Sander W. Keemink, Pablo Lanillos:
Closed-Form Control With Spike Coding Networks. IEEE Trans. Cogn. Dev. Syst. 16(5): 1677-1687 (2024) - [c2]an Schering, Sander W. Keemink, Johannes Textor:
Fitting Stochastic Lattice Models Using Approximate Gradients. ECMS 2024: 366-373 - [i4]Jesús García Fernández, Sander W. Keemink, Marcel van Gerven:
Gradient-Free Training of Recurrent Neural Networks using Random Perturbations. CoRR abs/2405.08967 (2024) - [i3]Sigur de Vries, Sander W. Keemink, Marcel van Gerven:
Discovering Dynamic Symbolic Policies with Genetic Programming. CoRR abs/2406.02765 (2024) - 2022
- [i2]Filip S. Slijkhuis, Sander W. Keemink, Pablo Lanillos:
Closed-form control with spike coding networks. CoRR abs/2212.12887 (2022) - 2020
- [c1]Allan Mancoo, Sander W. Keemink, Christian K. Machens:
Understanding spiking networks through convex optimization. NeurIPS 2020 - [i1]Michele Nardin, James W. Phillips, William F. Podlaski, Sander W. Keemink:
Nonlinear computations in spiking neural networks through multiplicative synapses. CoRR abs/2009.03857 (2020)
2010 – 2019
- 2018
- [j1]Sander W. Keemink, Dharmesh Tailor, Mark C. W. van Rossum:
Unconscious Biases in Neural Populations Coding Multiple Stimuli. Neural Comput. 30(12) (2018)
Coauthor Index
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