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07/24/2019
Knowledge transfer in deep block-modular neural networks
Although deep neural networks (DNNs) have demonstrated impressive result...
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07/24/2019
Learning abstract perceptual notions: the example of space
Humans are extremely swift learners. We are able to grasp highly abstrac...
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10/03/2018
Learning agent's spatial configuration from sensorimotor invariants
The design of robotic systems is largely dictated by our purely human in...
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10/03/2018
Learning an internal representation of the end-effector configuration space
Current machine learning techniques proposed to automatically discover a...
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06/07/2018
Discovering space - Grounding spatial topology and metric regularity in a naive agent's sensorimotor experience
In line with the sensorimotor contingency theory, we investigate the pro...
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11/28/2017
Block Neural Network Avoids Catastrophic Forgetting When Learning Multiple Task
In the present work we propose a Deep Feed Forward network architecture ...
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11/28/2017
Hyper-dimensional computing for a visual question-answering system that is trainable end-to-end
In this work we propose a system for visual question answering. Our arch...
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11/28/2017
Gradual Tuning: a better way of Fine Tuning the parameters of a Deep Neural Network
In this paper we present an alternative strategy for fine-tuning the par...
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08/09/2013
