6 citations · 6 across the 6 of their papers we have counts for
6 papers
BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training
Luca Colombo, Fabrizio Pittorino, Daniele Zambon +3
Binary Neural Networks (BNNs), which constrain both weights and activations to binary values, offer substantial reductions in computational complexity, memory footprint, and energy…
Dynamical Learning in Deep Asymmetric Recurrent Neural Networks
Davide Badalotti, Carlo Baldassi, Marc Mézard +2
We investigate recurrent neural networks with asymmetric interactions and demonstrate that the inclusion of self-couplings or sparse excitatory inter-module connections leads to th…
Generative diffusion for perceptron problems: statistical physics analysis and efficient algorithms
Elizaveta Demyanenko, Davide Straziota, Carlo Baldassi +1
We consider random instances of non-convex perceptron problems in the high-dimensional limit of a large number of examples and weights , with finite load . We develo…
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…
Algorithmic Decision Processes
Carlo Baldassi, Fabio Maccheroni, Massimo Marinacci +1
We develop a full-fledged analysis of an algorithmic decision process that, in a multialternative choice problem, produces computable choice probabilities and expected decision tim…
Theory and learning protocols for the material tempotron model
Carlo Baldassi, Alfredo Braunstein, Riccardo Zecchina
Neural networks are able to extract information from the timing of spikes. Here we provide new results on the behavior of the simplest neuronal model which is able to decode inform…