SAGLIETTI, LUCA
SAGLIETTI, LUCA
Dipartimento Scienza Applicata e Tecnologia
035651
Degradation Assessment for Prototypal Perovskite Photovoltaic Modules in Long Term Outdoor Experimental Campaign
2023 Aime, Giona; Ciocia, Alessandro; Malgaroli, Gabriele; Narbey, Stephanie; Saglietti, Luca; Spertino, Filippo
From inverse problems to learning: A Statistical Mechanics approach
2018 Baldassi, Carlo; Gerace, Federica; Saglietti, Luca; Zecchina, Riccardo
Out of equilibrium Statistical Physics of learning
2018 Saglietti, Luca
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 T; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; 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
Citazione | Data di pubblicazione | Autori | File |
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Degradation Assessment for Prototypal Perovskite Photovoltaic Modules in Long Term Outdoor Experimental Campaign / Aime, Giona; Ciocia, Alessandro; Malgaroli, Gabriele; Narbey, Stephanie; Saglietti, Luca; Spertino, Filippo. - (2023), pp. 1-5. (Intervento presentato al convegno 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023 tenutosi a Madrid (Spain) nel 06-09 June 2023) [10.1109/EEEIC/ICPSEurope57605.2023.10194854]. | 1-gen-2023 | Aime, GionaCiocia, AlessandroMalgaroli, GabrieleSaglietti, LucaSpertino, Filippo + | Degradation_Assessment_for_Prototypal_Perovskite_Photovoltaic_Modules_in_Long_Term_Outdoor_E.pdf; EEEIC23-PSC-degradation non editorial.pdf |
From inverse problems to learning: A Statistical Mechanics approach / Baldassi, Carlo; Gerace, Federica; Saglietti, Luca; Zecchina, Riccardo. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6588. - 955:1(2018), p. 012001. [10.1088/1742-6596/955/1/012001] | 1-gen-2018 | Baldassi, CarloGerace, FedericaSaglietti, LucaZecchina, Riccardo | - |
Out of equilibrium Statistical Physics of learning / Saglietti, Luca. - (2018 Apr 09). [10.6092/polito/porto/2710532] | 9-apr-2018 | SAGLIETTI, LUCA | PhDthesis_LucaSaglietti.pdf |
Learning may need only a few bits of synaptic precision / Baldassi, Carlo; Gerace, Federica; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo. - In: PHYSICAL REVIEW. E. - ISSN 2470-0045. - ELETTRONICO. - 93:5(2016), p. 052313. [10.1103/PhysRevE.93.052313] | 1-gen-2016 | BALDASSI, CARLOGERACE, FEDERICALUCIBELLO, CARLOSAGLIETTI, LUCAZECCHINA, RICCARDO | fewbits.pdf |
Local entropy as a measure for sampling solutions in constraint satisfaction problems / Baldassi, Carlo; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo. - In: JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT. - ISSN 1742-5468. - ELETTRONICO. - 2016:2(2016), p. 023301. [10.1088/1742-5468/2016/02/023301] | 1-gen-2016 | BALDASSI, CARLOINGROSSO, ALESSANDROLUCIBELLO, CARLOSAGLIETTI, LUCAZECCHINA, RICCARDO | - |
Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes / Baldassi, Carlo; Borgs, Christian; Chayes, Jennifer T; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo. - In: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA. - ISSN 0027-8424. - STAMPA. - 113:48(2016), pp. E7655-E7662. [10.1073/pnas.1608103113] | 1-gen-2016 | BALDASSI, CARLOINGROSSO, ALESSANDROLUCIBELLO, CARLOSAGLIETTI, LUCAZECCHINA, RICCARDO + | accessible-arxiv.pdf |
Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses / Baldassi, Carlo; Ingrosso, Alessandro; Lucibello, Carlo; Saglietti, Luca; Zecchina, Riccardo. - In: PHYSICAL REVIEW LETTERS. - ISSN 0031-9007. - ELETTRONICO. - 115:12(2015), p. 128101. [10.1103/PhysRevLett.115.128101] | 1-gen-2015 | BALDASSI, CARLOINGROSSO, ALESSANDROLUCIBELLO, CARLOSAGLIETTI, LUCAZECCHINA, RICCARDO | 1509.05753v1.pdf |