A Robotic Scenario for Programmable Fixed-Weight Neural Networks Exhibiting Multiple Behaviors. - Guglielmo Montone; Francesco Donnarumma; Roberto Prevete (ICANNGA (1), 2011)

Unsupervised model-free camera calibration algorithm for robotic applications. - Guglielmo Montone; J. Kevin O'Regan; Alexander V. Terekhov (IROS, 2015)

Knowledge Transfer in Deep Block-Modular Neural Networks. - Alexander V. Terekhov; Guglielmo Montone; J. Kevin O'Regan (Living Machines, 2015)

The Usefulness of Past Knowledge when Learning a New Task in Deep Neural Networks. - Guglielmo Montone; J. Kevin O'Regan; Alexander V. Terekhov (CoCo@NIPS, 2015)

Learning programs is better than learning dynamics: A programmable neural network hierarchical architecture in a multi-task scenario. - Francesco Donnarumma; Roberto Prevete; Andrea de Giorgio; Guglielmo Montone; Giovanni Pezzulo (Adapt. Behav., 2016)

Gradual Tuning: a better way of Fine Tuning the parameters of a Deep Neural Network. - Guglielmo Montone; J. Kevin O'Regan; Alexander V. Terekhov (CoRR, 2017)

Hyper-dimensional computing for a visual question-answering system that is trainable end-to-end. - Guglielmo Montone; J. Kevin O'Regan; Alexander V. Terekhov (CoRR, 2017)

Block Neural Network Avoids Catastrophic Forgetting When Learning Multiple Task. - Guglielmo Montone; J. Kevin O'Regan; Alexander V. Terekhov (CoRR, 2017)