A deep convolutional auto-encoder with pooling-unpooling layers in caffe

V Turchenko, E Chalmers, A Luczak - arXiv preprint arXiv:1701.04949, 2017 - arxiv.org
This paper presents the development of several models of a deep convolutional auto-
encoder in the Caffe deep learning framework and their experimental evaluation on the …

Neurons learn by predicting future activity

A Luczak, BL McNaughton, Y Kubo - Nature machine intelligence, 2022 - nature.com
Understanding how the brain learns may lead to machines with human-like intellectual
capacities. It was previously proposed that the brain may operate on the principle of …

Real-time classification of experience-related ensemble spiking patterns for closed-loop applications

D Ciliberti, F Michon, F Kloosterman - Elife, 2018 - elifesciences.org
Communication in neural circuits across the cortex is thought to be mediated by
spontaneous temporally organized patterns of population activity lasting~ 50–200 ms …