Learning in Neural Networks with Material Synapses
暂无分享,去创建一个
[1] Walter J. Freeman,et al. The Hebbian paradigm reintegrated: Local reverberations as internal representations , 1995, Behavioral and Brain Sciences.
[2] W. Krauth,et al. Storage capacity of memory networks with binary couplings , 1989 .
[3] David R. Cox,et al. The Theory of Stochastic Processes , 1967, The Mathematical Gazette.
[4] D. Amit,et al. Statistical mechanics of neural networks near saturation , 1987 .
[5] Frank der van Velde,et al. Association and computation with cell assemblies , 1995, Behavioral and Brain Sciences.
[6] David C. Krakauer,et al. An evolutionary perspective on Hebb's reverberatory representations , 1995, Behavioral and Brain Sciences.
[7] Gérard Weisbuch,et al. Scaling laws for the attractors of Hopfield networks , 1985 .
[8] James J. Wright,et al. How do local reverberations achieve global integration? , 1995, Behavioral and Brain Sciences.
[9] Gj Dalenoort,et al. What's in a cell assembly? , 1995, Behavioral and Brain Sciences.
[10] Y. Miyashita. Neuronal correlate of visual associative long-term memory in the primate temporal cortex , 1988, Nature.
[11] Josef P. Rauschecker,et al. Reverberations of Hebbian thinking , 1995, Behavioral and Brain Sciences.
[12] Davide Badoni,et al. Learning Attractor Neural Network: The Electronic Implementation , 1992, Int. J. Neural Syst..
[13] Peter C. M. Molenaar,et al. How to decide whether a neural representation is a cognitive concept? , 1995, Behavioral and Brain Sciences.
[14] H. C. LONGUET-HIGGINS,et al. Non-Holographic Associative Memory , 1969, Nature.
[15] Anders Lansner,et al. Distributed cell assemblies and detailed cell models , 1995, Behavioral and Brain Sciences.
[16] D. Amit. The Hebbian paradigm reintegrated: Local reverberations as internal representations , 1995, Behavioral and Brain Sciences.
[17] Daniel J. Amit,et al. Empirical and theoretical active memory: The proper context , 1995, Behavioral and Brain Sciences.
[18] Jacek Iwanski. Replica symmetry breaking calculation of the storage capacity of neural networks with discrete couplings , 1994 .
[19] G. Parisi. A memory which forgets , 1986 .
[20] Nicolas Brunel,et al. Adequate input for learning in attractor neural networks , 1993 .
[21] E. M.,et al. Statistical Mechanics , 2021, On Complementarity.
[22] Masahiko Morita,et al. Another ANN model for the Miyashita experiments , 1995, Behavioral and Brain Sciences.
[23] Edoardo Amaldi,et al. Stability-Capacity Diagram of a Neural Network with Ising Bonds , 1989 .
[24] Michael Hucka,et al. Hebb's accomplishments misunderstood , 1995, Behavioral and Brain Sciences.
[25] Joaquin M. Fuster,et al. Not the module does memory make – but the network , 1995, Behavioral and Brain Sciences.
[26] Hubert Preissl,et al. Local or transcortical assemblies? Some evidence from cognitive neuroscience , 1995, Behavioral and Brain Sciences.
[27] Daniel J. Amit,et al. Constraints on learning in dynamic synapses , 1992, Network: Computation in Neural Systems.
[28] Daniel J. Amit,et al. Conversion of Temporal Correlations Between Stimuli to Spatial Correlations Between Attractors , 1999, Neural Computation.
[29] H. Gutfreund,et al. Capacity of neural networks with discrete synaptic couplings , 1990 .
[30] Shimon Edelman,et al. What's in a cell assembly? , 1995, Behavioral and Brain Sciences.
[31] D. Amit,et al. Constraints on learning in dynamic synapses , 1992 .
[32] Eric Chown,et al. Reverberation reconsidered: On the path to cognitive theory , 1995, Behavioral and Brain Sciences.
[33] Morris W. Hirsch,et al. Mathematics of Hebbian attractors , 1995, Behavioral and Brain Sciences.
[34] Wolfgang Klimesch,et al. The functional meaning of reverberations for sensoric and contextual encoding , 1995, Behavioral and Brain Sciences.
[35] Stanislas Dehaene,et al. Networks of Formal Neurons and Memory Palimpsests , 1986 .
[36] P. Milner,et al. Attractors – don't get sucked in , 1995, Behavioral and Brain Sciences.
[37] Ralph E. Hoffman,et al. Additional tests of Amit's attractor neural networks , 1995, Behavioral and Brain Sciences.
[38] I. I. Gikhman. Theory of stochastic processes , 1974 .
[39] Jean Petitot,et al. The problems of cognitive dynamical models , 1995, Behavioral and Brain Sciences.
[40] M. Tsodyks. ASSOCIATIVE MEMORY IN NEURAL NETWORKS WITH BINARY SYNAPSES , 1990 .
[41] Elie Bienenstock,et al. Where the adventure is , 1995, Behavioral and Brain Sciences.
[42] N. S. Barnett,et al. Private communication , 1969 .
[43] Ehud Ahissar,et al. Are single-cell data sufficient for testing neural network models? , 1995, Behavioral and Brain Sciences.
[44] 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.
[45] K. Stratford,et al. Synaptic transmission between individual pyramidal neurons of the rat visual cortex in vitro , 1991, The Journal of neuroscience : the official journal of the Society for Neuroscience.