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cs.CC2022
Parameterized Complexity Results for Bayesian Inference
Hans Bodlaender, Nils Donselaar, Johan Kwisthout
We present completeness results for inference in Bayesian networks with respect to two different parameterizations, namely the number of variables and the topological vertex separa…
cs.CC2020
On the computational power and complexity of Spiking Neural Networks
Johan Kwisthout, Nils Donselaar
The last decade has seen the rise of neuromorphic architectures based on artificial spiking neural networks, such as the SpiNNaker, TrueNorth, and Loihi systems. The massive parall…
cs.CC2018
Finding dissimilar explanations in Bayesian networks: Complexity results
Johan Kwisthout
Finding the most probable explanation for observed variables in a Bayesian network is a notoriously intractable problem, particularly if there are hidden variables in the network.…