Department of Electrical and Electronic Engineering
London SW7 2AZ
Nicolas Perez is a PhD student working on understanding how spiking neural networks can use heterogeneous neuron properties to carry out multiresolution processing of sensory data.
Note that only publications as part of the Neural Reckoning group are included here (see external publications below for full list).
Perez-Nieves N, Leung VCH, Dragotti PL, Goodman DFM (2021)
Neural heterogeneity promotes robust learning.
Perez-Nieves N, Leung VCH, Dragotti PL, Goodman DFM (2019)
Advantages of heterogeneity of parameters in spiking neural network training.
Cognitive Computational Neuroscience
- + 1 conference paper
- D. Mguni, et al. (2021)
Learning to Shape Rewards using a Game of Switching Controls