Sfoglia per Autore ZECCHINA, RICCARDO
Efficient supervised learning in networks with binary synapses
2007 Baldassi, Carlo; Braunstein, Alfredo; Brunel, Nicolas; Zecchina, Riccardo
Efficient supervised learning in networks with binary synapses
2007 Baldassi, Carlo; Braunstein, Alfredo; Brunel, Nicolas; Zecchina, Riccardo
From luminance to semantics: how natural objects are represented in monkey inferotemporal cortex.
2011 Marino, Pagan; Alireza Alemi, Neissi; Baldassi, Carlo; Zecchina, Riccardo; James, Dicarlo; Davide, Zoccolan
Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition
2012 Alireza Alemi, Neissi; Baldassi, Carlo; Alfredo, Braunstein; Andrea, Pagnani; Zecchina, Riccardo; Davide, Zoccolan
Theory and learning protocols for the material tempotron model
2013 Baldassi, Carlo; Braunstein, Alfredo; Zecchina, Riccardo
Shape similarity, better than semantic membership, accounts for the structure of visual object representations in a population of monkey inferotemporal neurons
2013 Baldassi, Carlo; Alemi Neissi, Alireza; Pagan, Marino; Dicarlo, James J.; Zecchina, Riccardo; Zoccolan, Davide
Input-driven unsupervised learning in recurrent neural networks
2014 Alireza Alemi, Neissi; Baldassi, Carlo; Nicolas, Brunel; Zecchina, Riccardo
Fast and accurate multivariate Gaussian modeling of protein families: predicting residue contacts and protein-interaction partners
2014 Baldassi, Carlo; Zamparo, Marco; Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea
Sharing information to reconstruct patient-specific pathways in heterogeneous diseases
2014 Gitter, Anthony; Braunstein, Alfredo; Pagnani, Andrea; Baldassi, Carlo; Borgs, Christian; Chayes, Jennifer; Zecchina, Riccardo; Fraenkel, Ernest
Statistical physics and network optimization problems
2015 Baldassi, Carlo; Braunstein, Alfredo; Ramezanpour, Abolfazl; Zecchina, Riccardo
Subdominant dense clusters allow for simple learning and high computational performance in neural networks with discrete synapses
2015 Baldassi, Carlo; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo
A three-threshold learning rule approaches the maximal capacity of recurrent neural networks
2015 Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo
Learning may need only a few bits of synaptic precision
2016 Baldassi, Carlo; Gerace, Federica; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo
Local entropy as a measure for sampling solutions in constraint satisfaction problems
2016 Baldassi, Carlo; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo
Unreasonable effectiveness of learning neural networks: from accessible states and robust ensembles to basic algorithmic schemes
2016 Baldassi, Carlo; Borgs, Christian; Chayes, Jennifer; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo
RNAs competing for microRNAs mutually influence their fluctuations in a highly non-linear microRNA-dependent manner in single cells
2017 Bosia, Carla; Conti, Francesco; Sgrò, Laura; Baldassi, Carlo; Brusa, Davide; Cavallo, Federica; Di Cunto, Ferdinando; Turco, Emilia; Pagnani, Andrea; Zecchina, Riccardo
Inverse statistical problems: from the inverse Ising problem to data science
2017 Nguyen, H. Chau; Zecchina, Riccardo; Berg, Johannes
From inverse problems to learning: a statistical mechanics approach
2018 Baldassi, Carlo; Gerace, Federica; Saglietti, Luca; Zecchina, Riccardo
From statistical inference to a differential learning rule for stochastic neural networks
2018 Saglietti, Luca; Gerace, Federica; Ingrosso, Alessandro; Baldassi, Carlo; Zecchina, Riccardo
Role of synaptic stochasticity in training low-precision neural networks
2018 Baldassi, Carlo; Gerace, Federica; Kappen, Hilbert J.; Lucibello, Carlo; Saglietti, Luca; Tartaglione, Enzo; Zecchina, Riccardo
Titolo | Data di pubblicazione | Autore(i) | Rivista | Editore |
---|---|---|---|---|
Efficient supervised learning in networks with binary synapses | 1-gen-2007 | Baldassi, Carlo; Braunstein, Alfredo; Brunel, Nicolas; Zecchina, Riccardo | - | NATL ACAD SCIENCES |
Efficient supervised learning in networks with binary synapses | 1-gen-2007 | Baldassi, Carlo; Braunstein, Alfredo; Brunel, Nicolas; Zecchina, Riccardo | PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | - |
From luminance to semantics: how natural objects are represented in monkey inferotemporal cortex. | 1-gen-2011 | Marino, Pagan; Alireza Alemi, Neissi; Baldassi, Carlo; Zecchina, Riccardo; James, Dicarlo; Davide, Zoccolan | - | COSYNE |
Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition | 1-gen-2012 | Alireza Alemi, Neissi; Baldassi, Carlo; Alfredo, Braunstein; Andrea, Pagnani; Zecchina, Riccardo; Davide, Zoccolan | BMC NEUROSCIENCE | BioMed Central Ltd |
Theory and learning protocols for the material tempotron model | 1-gen-2013 | Baldassi, Carlo; Braunstein, Alfredo; Zecchina, Riccardo | JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT | - |
Shape similarity, better than semantic membership, accounts for the structure of visual object representations in a population of monkey inferotemporal neurons | 1-gen-2013 | Baldassi, Carlo; Alemi Neissi, Alireza; Pagan, Marino; Dicarlo, James J.; Zecchina, Riccardo; Zoccolan, Davide | PLOS COMPUTATIONAL BIOLOGY | - |
Input-driven unsupervised learning in recurrent neural networks | 1-gen-2014 | Alireza Alemi, Neissi; Baldassi, Carlo; Nicolas, Brunel; Zecchina, Riccardo | - | COSYNE |
Fast and accurate multivariate Gaussian modeling of protein families: predicting residue contacts and protein-interaction partners | 1-gen-2014 | Baldassi, Carlo; Zamparo, Marco; Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea | PLOS ONE | - |
Sharing information to reconstruct patient-specific pathways in heterogeneous diseases | 1-gen-2014 | Gitter, Anthony; Braunstein, Alfredo; Pagnani, Andrea; Baldassi, Carlo; Borgs, Christian; Chayes, Jennifer; Zecchina, Riccardo; Fraenkel, Ernest | - | World Scientific Pub. Co. |
Statistical physics and network optimization problems | 1-gen-2015 | Baldassi, Carlo; Braunstein, Alfredo; Ramezanpour, Abolfazl; Zecchina, Riccardo | - | Springer International Publishing |
Subdominant dense clusters allow for simple learning and high computational performance in neural networks with discrete synapses | 1-gen-2015 | Baldassi, Carlo; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo | PHYSICAL REVIEW LETTERS | - |
A three-threshold learning rule approaches the maximal capacity of recurrent neural networks | 1-gen-2015 | Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo | PLOS COMPUTATIONAL BIOLOGY | - |
Learning may need only a few bits of synaptic precision | 1-gen-2016 | Baldassi, Carlo; Gerace, Federica; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo | PHYSICAL REVIEW. E | - |
Local entropy as a measure for sampling solutions in constraint satisfaction problems | 1-gen-2016 | Baldassi, Carlo; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo | JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT | - |
Unreasonable effectiveness of learning neural networks: from accessible states and robust ensembles to basic algorithmic schemes | 1-gen-2016 | Baldassi, Carlo; Borgs, Christian; Chayes, Jennifer; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo | PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | - |
RNAs competing for microRNAs mutually influence their fluctuations in a highly non-linear microRNA-dependent manner in single cells | 1-gen-2017 | Bosia, Carla; Conti, Francesco; Sgrò, Laura; Baldassi, Carlo; Brusa, Davide; Cavallo, Federica; Di Cunto, Ferdinando; Turco, Emilia; Pagnani, Andrea; Zecchina, Riccardo | GENOME BIOLOGY | - |
Inverse statistical problems: from the inverse Ising problem to data science | 1-gen-2017 | Nguyen, H. Chau; Zecchina, Riccardo; Berg, Johannes | ADVANCES IN PHYSICS | - |
From inverse problems to learning: a statistical mechanics approach | 1-gen-2018 | Baldassi, Carlo; Gerace, Federica; Saglietti, Luca; Zecchina, Riccardo | - | Institute of Physics Publishing |
From statistical inference to a differential learning rule for stochastic neural networks | 1-gen-2018 | Saglietti, Luca; Gerace, Federica; Ingrosso, Alessandro; Baldassi, Carlo; Zecchina, Riccardo | INTERFACE FOCUS | - |
Role of synaptic stochasticity in training low-precision neural networks | 1-gen-2018 | Baldassi, Carlo; Gerace, Federica; Kappen, Hilbert J.; Lucibello, Carlo; Saglietti, Luca; Tartaglione, Enzo; Zecchina, Riccardo | PHYSICAL REVIEW LETTERS | - |
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