70 citations · 70 across the 5 of their papers we have counts for
7 papers
Cross-Modal Visuo-Tactile Object Perception
Anirvan Dutta, Simone Tasciotti, Claudia Cusseddu +6
Estimating physical properties is critical for safe and efficient autonomous robotic manipulation, particularly during contact-rich interactions. In such settings, vision and tacti…
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…
Leveraging dendritic properties to advance machine learning and neuro-inspired computing
Michalis Pagkalos, Roman Makarov, Panayiota Poirazi
The brain is a remarkably capable and efficient system. It can process and store huge amounts of noisy and unstructured information using minimal energy. In contrast, current artif…
Dendrites and Efficiency: Optimizing Performance and Resource Utilization
Roman Makarov, Michalis Pagkalos, Panayiota Poirazi
The brain is a highly efficient system evolved to achieve high performance with limited resources. We propose that dendrites make information processing and storage in the brain mo…
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…