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Ala U, Karreth FA, Bosia C, Pagnani A, Taulli R, Léopold V, et al. Integrated transcriptional and competitive endogenous RNA networks are cross-regulated in permissive molecular environments . Proceedings of the National Academy of Sciences of the United States of America. 2013;110(18).
Alemi A, Baldassi C, Brunel N, Zecchina R. A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks. PLoS Comput Biol. 2015;11:1-23.
Alemi-Neissi A, Baldassi C, Braunstein A, Pagnani A, Zecchina R, Zoccolan D. Information theoretic and machine learning approaches to quantify non-linear visual feature interaction underlying visual object recognition. BMC Neuroscience. 2012;13:1-2.
Altarelli F, Braunstein A, Ramezanpour A, Zecchina R. Stochastic optimization by message passing. JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT. 2011;2011. Abstract
Altarelli F, Braunstein A, Realpe-Gomez J, Zecchina R. Statistical mechanics of budget-constrained auctions. Journal of Statistical Mechanics: Theory and Experiment. 2009;2009:P07002 (27pp). Abstract
Altarelli F, Braunstein A, Ramezanpour A, Zecchina R. Stochastic Matching Problem. Phys. Rev. Lett.. 2011;106:190601.
Altarelli F, Braunstein A, Dall'Asta L, Zecchina R. Large deviations of cascade processes on graphs. Phys. Rev. E. 2013;87:062115.
Altarelli F, Braunstein A, Dall’Asta L, Lage-Castellanos A, Zecchina R. Bayesian Inference of Epidemics on Networks via Belief Propagation. Physical Review Letters. 2014;112(11).
Altarelli F, Braunstein A, Dall’Asta L, Ingrosso A, Zecchina R. The patient-zero problem with noisy observations. Journal of Statistical Mechanics: Theory and Experiment. 2014;2014:P10016.
Altarelli F, Braunstein A, Dall’Asta L, Ingrosso A, Zecchina R. The patient-zero problem with noisy observations. Journal of Statistical Mechanics: Theory and Experiment. 2014;2014(10):P10016.
Altarelli F, Braunstein A, Dall’Asta L, Zecchina R. Optimizing spread dynamics on graphs by message passing. Journal of Statistical Mechanics: Theory and Experiment. 2013;2013(09):P09011.
Altman RB, Dunker KA, Hunter L, Murray TA, Klein TE, Ritchie MD, et al. Sharing Information to reconstruct patient-specific pathways in heterogeneous diseases. In: Biocomputing 2014. WORLD SCIENTIFIC; 2013. p. 39-50.
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Bailly-Bechet M, Borgs C, Braunstein A, Chayes J, Dagkessamanskaia A, François JM, et al. Finding undetected protein associations in cell signaling by belief propagation. Proceedings of the National Academy of Sciences. 2010;108(2):882-7. Abstract  Download: PNAS-2011-Bailly-Bechet-882-7.pdf (324.11 KB)
Bailly-Bechet M, Bradde S, Braunstein A, Flaxman A, Foini L, Zecchina R. Clustering with shallow trees. JSTAT. 2009:17pp. Abstract
Bailly-Bechet M, Braunstein A, Zecchina R. A Prize-Collecting Steiner Tree Approach for Transduction Network Inference. In: Proceedings of the 7th International Conference on Computational Methods in Systems Biology. Springer; 2009. 95.
Bailly-Bechet M, Benecke A, Hardt WD, Lanza V, Sturm A, Zecchina R. An externally modulated, noise-driven switch for the regulation of SPI1 in Salmonella enterica serovar Typhimurium. Journal of Mathematical Biology. 2011;63:637-62.
Bailly-Bechet M, Braunstein A, Pagnani A, Weigt M, Zecchina R. Inference of sparse combinatorial-control networks from gene-expression data: a message passing approach. BMC bioinformatics. 2010;11:355. Abstract
Baldassi C, Zamparo M, Feinauer C, Procaccini A, Zecchina R, Weigt M, et al. Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners. PLoS ONE. 2014;9(3):e92721. Abstract
Baldassi C, Braunstein A, Brunel N, Zecchina R. Efficient supervised learning in networks with binary synapses. Proceedings of the National Academy of Sciences. 2007;104:11079-84.
Baldassi C, Ingrosso A, Lucibello C, Saglietti L, Zecchina R. Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses. Physical review letters. 2015;115:128101.
Baldassi C, Braunstein A, Zecchina R. Theory and learning protocols for the material tempotron model. Journal of Statistical Mechanics: Theory and Experiment. 2013;2013(12):P12013.
Baldassi C, Alemi-Neissi A, Pagan M, Dicarlo JJ, Zecchina R, Zoccolan D. Shape similarity, better than semantic membership, accounts for the structure of visual object representations in a population of monkey inferotemporal neurons. PLoS Comput Biol. 2013;9(8):e1003167. Abstract
Baldassi C, Braunstein A, Brunel N, Zecchina R. Efficient supervised learning in networks with binary synapses. BMC Neuroscience. 2007;8:S13.
Baldassi C, Ingrosso A, Lucibello C, Saglietti L, Zecchina R. Local entropy as a measure for sampling solutions in constraint satisfaction problems. Journal of Statistical Mechanics: Theory and Experiment. 2016;2016:023301. Abstract
Battaglia D, Braunstein A, Chavas J, Zecchina R. Source coding by efficient selection of ground-state clusters. Phys Rev E. Stat Nonlin Soft Matter Phys. 2005;72:015103.