SilicoPharm
Polypharmacological in silico screening platform for the next generation drugs

Publication

M. Wołczyk , J. Tabor , M. Śmieja , and S. Maszke
Biologically-Inspired Spatial Neural Networks
arXiv, 2019
URL, RIS, BibTex

Abstract

We introduce bio-inspired artificial neural networks consisting of neurons that are additionally characterized by spatial positions. To simulate properties of biological systems we add the costs penalizing long connections and the proximity of neurons in a two-dimensional space. Our experiments show that in the case where the network performs two different tasks, the neurons naturally split into clusters, where each cluster is responsible for processing a different task. This behavior not only corresponds to the biological systems, but also allows for further insight into interpretability or continual learning.

Reference

@article{Wołczyk2019a,
  author = "M. Wołczyk and J. Tabor and M. Śmieja and S. Maszke",
  title = "Biologically-Inspired Spatial Neural Networks",
  year = 2019,
  journal = "arXiv",
  url = "http://arxiv.org/abs/1910.02776"
}