89 citations · 167 across the 9 of their papers we have counts for
9 papers
Impact of dendritic non-linearities on the computational capabilities of neurons
Clarissa Lauditi, Enrico M. Malatesta, Fabrizio Pittorino +3
How neurons integrate the myriad synaptic inputs scattered across their dendrites is a fundamental question in neuroscience. Multiple neurophysiological experiments have shown that…
The star-shaped space of solutions of the spherical negative perceptron
Brandon Livio Annesi, Clarissa Lauditi, Carlo Lucibello +4
Empirical studies on the landscape of neural networks have shown that low-energy configurations are often found in complex connected structures, where zero-energy paths between pai…
Deep Networks on Toroids: Removing Symmetries Reveals the Structure of Flat Regions in the Landscape Geometry
Fabrizio Pittorino, Antonio Ferraro, Gabriele Perugini +3
We systematize the approach to the investigation of deep neural network landscapes by basing it on the geometry of the space of implemented functions rather than the space of param…
Deep learning via message passing algorithms based on belief propagation
Carlo Lucibello, Fabrizio Pittorino, Gabriele Perugini +1
Message-passing algorithms based on the Belief Propagation (BP) equations constitute a well-known distributed computational scheme. It is exact on tree-like graphical models and ha…
Order symmetry breaking and broad distribution of events in spiking neural networks with continuous membrane potential
Marco Stucchi, Fabrizio Pittorino, Matteo di Volo +2
We introduce an exactly integrable version of the well-known leaky integrate-and-fire (LIF) model, with continuous membrane potential at the spiking event, the c-LIF. We investigat…
Entropic gradient descent algorithms and wide flat minima
Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer +4
The properties of flat minima in the empirical risk landscape of neural networks have been debated for some time. Increasing evidence suggests they possess better generalization ca…
Shaping the learning landscape in neural networks around wide flat minima
Carlo Baldassi, Fabrizio Pittorino, Riccardo Zecchina
Learning in Deep Neural Networks (DNN) takes place by minimizing a non-convex high-dimensional loss function, typically by a stochastic gradient descent (SGD) strategy. The learnin…
Chaos and correlated avalanches in excitatory neural networks with synaptic plasticity
Fabrizio Pittorino, Miguel Ibáñez-Berganza, Matteo di Volo +2
A collective chaotic phase with power law scaling of activity events is observed in a disordered mean field network of purely excitatory leaky integrate-and-fire neurons with short…
Nonsingular cosmology from evolutionary quantum gravity
Francesco Cianfrani, Giovanni Montani, Fabrizio Pittorino
We provide a cosmological implementation of the evolutionary quantum gravity, describing an isotropic Universe, in the presence of a negative cosmological constant and a massive (p…