70 citations · 71 across the 3 of their papers we have counts for
4 papers
Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning
Spyridon Chavlis, Panayiota Poirazi
Artificial neural networks (ANNs) are at the core of most Deep learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and na…
Dendritic Self-Organizing Maps for Continual Learning
Kosmas Pinitas, Spyridon Chavlis, Panayiota Poirazi
Current deep learning architectures show remarkable performance when trained in large-scale, controlled datasets. However, the predictive ability of these architectures significant…
Drawing Inspiration from Biological Dendrites to Empower Artificial Neural Networks
Spyridon Chavlis, Panayiota Poirazi
This article highlights specific features of biological neurons and their dendritic trees, whose adoption may help advance artificial neural networks used in various machine learni…
Artificial neural networks in action for an automated cell-type classification of biological neural networks
Eirini Troullinou, Grigorios Tsagkatakis, Spyridon Chavlis +5
Identification of different neuronal cell types is critical for understanding their contribution to brain functions. Yet, automated and reliable classification of neurons remains a…