The emergence of a concept in shallow neural networks
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Elena Agliari | Adriano Barra | Giordano De Marzo | Francesco Alemanno | A. Barra | E. Agliari | Francesco Alemanno
[1] Elena Agliari,et al. Multitasking associative networks. , 2011, Physical review letters.
[2] C. Gross. Genealogy of the “Grandmother Cell” , 2002, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.
[3] Cristopher Moore,et al. The Nature of Computation , 2011 .
[4] Andrea Montanari,et al. A mean field view of the landscape of two-layer neural networks , 2018, Proceedings of the National Academy of Sciences.
[5] M. Mézard,et al. Analytic and Algorithmic Solution of Random Satisfiability Problems , 2002, Science.
[6] J J Hopfield,et al. Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.
[7] Adriano Barra,et al. On the equivalence of Hopfield Networks and Restricted Boltzmann Machines , 2011, ArXiv.
[8] Sompolinsky,et al. Storing infinite numbers of patterns in a spin-glass model of neural networks. , 1985, Physical review letters.
[9] Peter Sollich,et al. Theory of Neural Information Processing Systems , 2005 .
[10] Giancarlo Fissore,et al. Thermodynamics of Restricted Boltzmann Machines and Related Learning Dynamics , 2018, Journal of Statistical Physics.
[11] Elena Agliari,et al. Machine learning and statistical physics: preface , 2020, Journal of Physics A: Mathematical and Theoretical.
[12] José F. Fontanari,et al. Generalization in a Hopfield network , 1990 .
[13] Haiping Huang. Variational mean-field theory for training restricted Boltzmann machines with binary synapses. , 2020, Physical review. E.
[14] Rémi Monasson,et al. Emergence of Compositional Representations in Restricted Boltzmann Machines , 2016, Physical review letters.
[15] Florent Krzakala,et al. Statistical physics-based reconstruction in compressed sensing , 2011, ArXiv.
[16] Elena Agliari,et al. On the effective initialisation for restricted Boltzmann machines via duality with Hopfield model , 2021, Neural Networks.
[17] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[18] M. Mézard. Mean-field message-passing equations in the Hopfield model and its generalizations. , 2016, Physical review. E.
[19] F. Guerra. Broken Replica Symmetry Bounds in the Mean Field Spin Glass Model , 2002, cond-mat/0205123.
[20] Elena Agliari,et al. Neural Networks with a Redundant Representation: Detecting the Undetectable. , 2019, Physical review letters.
[21] Geoffrey E. Hinton,et al. Deep Boltzmann Machines , 2009, AISTATS.
[22] Jeffrey S. Bowers,et al. What is a grandmother cell? And how would you know if you found one? , 2011, Connect. Sci..
[23] Elena Agliari,et al. Boltzmann Machines as Generalized Hopfield Networks: A Review of Recent Results and Outlooks , 2020, Entropy.
[24] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[25] Haiping Huang,et al. Statistical physics of unsupervised learning with prior knowledge in neural networks , 2019, Physical review letters.
[26] Geoffrey E. Hinton,et al. A Learning Algorithm for Boltzmann Machines , 1985, Cogn. Sci..
[27] Sompolinsky,et al. Statistical mechanics of learning from examples. , 1992, Physical review. A, Atomic, molecular, and optical physics.
[28] Haiping Huang,et al. Statistical mechanics of unsupervised feature learning in a restricted Boltzmann machine with binary synapses , 2016, ArXiv.