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Carlo Baldassi

Showing results (1-10 of 19) with videos related to

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Proceedings of the National Academy of Sciences of the United States of America|February 1, 2018
Efficiency of quantum vs. classical annealing in nonconvex learning problemsCarlo Baldassi, Riccardo Zecchina
Proceedings of the National Academy of Sciences of the United States of America|December 25, 2019
Shaping the learning landscape in neural networks around wide flat minimaCarlo Baldassi, Fabrizio Pittorino, Riccardo Zecchina
Physical Review Letters|November 9, 2019
Properties of the Geometry of Solutions and Capacity of Multilayer Neural Networks with Rectified Linear Unit ActivationsCarlo Baldassi, Enrico M Malatesta, Riccardo Zecchina
Methods in Molecular Biology (Clifton, N.J.)|October 5, 2019
Predicting Interacting Protein Pairs by Coevolutionary Paralog MatchingThomas Gueudré, Carlo Baldassi, Andrea Pagnani, et al.
Proceedings of the National Academy of Sciences of the United States of America|June 22, 2007
Efficient supervised learning in networks with binary synapsesCarlo Baldassi, Alfredo Braunstein, Nicolas Brunel, et al.
Plos Computational Biology|August 21, 2015
A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural NetworksAlireza Alemi, Carlo Baldassi, Nicolas Brunel, et al.
Physical Review. E|September 19, 2023
Typical and atypical solutions in nonconvex neural networks with discrete and continuous weightsCarlo Baldassi, Enrico M Malatesta, Gabriele Perugini, et al.
Physical Review Letters|October 3, 2015
Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete SynapsesCarlo Baldassi, Alessandro Ingrosso, Carlo Lucibello, et al.
Physical Review. E|June 15, 2016
Learning may need only a few bits of synaptic precisionCarlo Baldassi, Federica Gerace, Carlo Lucibello, et al.
Interface Focus|November 17, 2018
From statistical inference to a differential learning rule for stochastic neural networksLuca Saglietti, Federica Gerace, Alessandro Ingrosso, et al.
Pageof 2

Showing results (1-10 of 19) with videos related to

Sort By:
Pageof 2
Proceedings of the National Academy of Sciences of the United States of America|February 1, 2018
Efficiency of quantum vs. classical annealing in nonconvex learning problemsCarlo Baldassi, Riccardo Zecchina
Proceedings of the National Academy of Sciences of the United States of America|December 25, 2019
Shaping the learning landscape in neural networks around wide flat minimaCarlo Baldassi, Fabrizio Pittorino, Riccardo Zecchina
Physical Review Letters|November 9, 2019
Properties of the Geometry of Solutions and Capacity of Multilayer Neural Networks with Rectified Linear Unit ActivationsCarlo Baldassi, Enrico M Malatesta, Riccardo Zecchina
Methods in Molecular Biology (Clifton, N.J.)|October 5, 2019
Predicting Interacting Protein Pairs by Coevolutionary Paralog MatchingThomas Gueudré, Carlo Baldassi, Andrea Pagnani, et al.
Proceedings of the National Academy of Sciences of the United States of America|June 22, 2007
Efficient supervised learning in networks with binary synapsesCarlo Baldassi, Alfredo Braunstein, Nicolas Brunel, et al.
Plos Computational Biology|August 21, 2015
A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural NetworksAlireza Alemi, Carlo Baldassi, Nicolas Brunel, et al.
Physical Review. E|September 19, 2023
Typical and atypical solutions in nonconvex neural networks with discrete and continuous weightsCarlo Baldassi, Enrico M Malatesta, Gabriele Perugini, et al.
Physical Review Letters|October 3, 2015
Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete SynapsesCarlo Baldassi, Alessandro Ingrosso, Carlo Lucibello, et al.
Physical Review. E|June 15, 2016
Learning may need only a few bits of synaptic precisionCarlo Baldassi, Federica Gerace, Carlo Lucibello, et al.
Interface Focus|November 17, 2018
From statistical inference to a differential learning rule for stochastic neural networksLuca Saglietti, Federica Gerace, Alessandro Ingrosso, et al.
Pageof 2