29 citations · 58 across the 8 of their papers we have counts for
8 papers
Can Machines Philosophize?
Michele Pizzochero, Giorgia Dellaferrera
Inspired by the Turing test, we present a novel methodological framework to assess the extent to which a population of machines mirrors the philosophical views of a population of h…
Intrinsic Biologically Plausible Adversarial Robustness
Matilde Tristany Farinha, Thomas Ortner, Giorgia Dellaferrera +2
Artificial Neural Networks (ANNs) trained with Backpropagation (BP) excel in different daily tasks but have a dangerous vulnerability: inputs with small targeted perturbations, als…
Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization
Ravi Srinivasan, Francesca Mignacco, Martino Sorbaro +4
"Forward-only" algorithms, which train neural networks while avoiding a backward pass, have recently gained attention as a way of solving the biologically unrealistic aspects of ba…
Modeling the Repetition-based Recovering of Acoustic and Visual Sources with Dendritic Neurons
Giorgia Dellaferrera, Toshitake Asabuki, Tomoki Fukai
In natural auditory environments, acoustic signals originate from the temporal superimposition of different sound sources. The problem of inferring individual sources from ambiguou…
Learning in Deep Neural Networks Using a Biologically Inspired Optimizer
Giorgia Dellaferrera, Stanislaw Wozniak, Giacomo Indiveri +2
Plasticity circuits in the brain are known to be influenced by the distribution of the synaptic weights through the mechanisms of synaptic integration and local regulation of synap…
Fooling the primate brain with minimal, targeted image manipulation
Li Yuan, Will Xiao, Giorgia Dellaferrera +4
Artificial neural networks (ANNs) are considered the current best models of biological vision. ANNs are the best predictors of neural activity in the ventral stream; moreover, rece…
A Bin Encoding Training of a Spiking Neural Network-based Voice Activity Detection
Giorgia Dellaferrera, Flavio Martinelli, Milos Cernak
Advances of deep learning for Artificial Neural Networks(ANNs) have led to significant improvements in the performance of digital signal processing systems implemented on digital c…
Spiking neural networks trained with backpropagation for low power neuromorphic implementation of voice activity detection
Flavio Martinelli, Giorgia Dellaferrera, Pablo Mainar +1
Recent advances in Voice Activity Detection (VAD) are driven by artificial and Recurrent Neural Networks (RNNs), however, using a VAD system in battery-operated devices requires fu…