2 citations · 3 across the 4 of their papers we have counts for
4 papers
Programming molecular systems to emulate a learning spiking neuron
Jakub Fil, Neil Dalchau, Dominique Chu
Hebbian theory seeks to explain how the neurons in the brain adapt to stimuli, to enable learning. An interesting feature of Hebbian learning is that it is an unsupervised method a…
A thermodynamically consistent chemical spiking neuron capable of autonomous Hebbian learning
Jakub Fil, Dominique Chu
We propose a fully autonomous, thermodynamically consistent set of chemical reactions that implements a spiking neuron. This chemical neuron is able to learn input patterns in a He…
Minimal spiking neuron for solving multi-label classification tasks
Jakub Fil, Dominique Chu
The Multi-Spike Tempotron (MST) is a powerful single spiking neuron model that can solve complex supervised classification tasks. While powerful, it is also internally complex, com…
MultiNet: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery
Tim G. J. Rudner, Marc Rußwurm, Jakub Fil +4
We propose a novel approach for rapid segmentation of flooded buildings by fusing multiresolution, multisensor, and multitemporal satellite imagery in a convolutional neural networ…