Journal de Physique

Response : Computing with Neural Networks

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Inhomogeneities in Heteroassociative Memories with Linear Learning Rules

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Neural Computation 20 (2) 311 (2008)
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Layered feed-forward neural network with exactly soluble dynamics

Ronny Meir and Eytan Domany
Physical Review A 37 (2) 608 (1988)
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Potts-glass models of neural networks

Ido Kanter
Physical Review A 37 (7) 2739 (1988)
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Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization

Michael Biehl, Fthi Abadi, Christina Göpfert and Barbara Hammer
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Introduction to neural network models

B. Derrida
Nuclear Physics B - Proceedings Supplements 4 673 (1988)
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Soft-bound Synaptic Plasticity Increases Storage Capacity

Mark C. W. van Rossum, Maria Shippi, Adam B. Barrett and Peter E. Latham
PLoS Computational Biology 8 (12) e1002836 (2012)
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Retrieval Properties of Neural Networks with Infinitely Many Marked Patterns

S Nicolis
Europhysics Letters (EPL) 12 (7) 583 (1990)
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Paramagnetic unlearning in neural network models

Kazuo Nokura
Physical Review E 54 (5) 5571 (1996)
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Maximum Storage Capacity in Neural Networks

E Gardner
Europhysics Letters (EPL) 4 (4) 481 (1987)
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Information storage in neural networks with low levels of activity

Daniel J. Amit, Hanoch Gutfreund and H. Sompolinsky
Physical Review A 35 (5) 2293 (1987)
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Domain Theory in Learning Processes

A. Edalat
Electronic Notes in Theoretical Computer Science 1 114 (1995)
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Associative Memory for Online Learning in Noisy Environments Using Self-Organizing Incremental Neural Network

A. Sudo, A. Sato and O. Hasegawa
IEEE Transactions on Neural Networks 20 (6) 964 (2009)
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Principal component analysis for fermionic critical points

Natanael C. Costa, Wenjian Hu, Z. J. Bai, Richard T. Scalettar and Rajiv R. P. Singh
Physical Review B 96 (19) (2017)
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Recall of old and recent information

Vipin Srivastava, Meena Vipin and Enzo Granato
Network: Computation in Neural Systems 9 (2) 159 (1998)
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A memory model with novel behaviour in sequential learning

P E Kahn, K Y M Wong and D Sherrington
Network: Computation in Neural Systems 6 (3) 415 (1995)
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Constraints on learning in dynamic synapses

Daniel J Amit and Stefano Fusi
Network: Computation in Neural Systems 3 (4) 443 (1992)
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Effects of temporary synaptic strengthening and residual cell potential in the retrieval of patterns

Tohru Nakano and Osamu Moriyama
Network: Computation in Neural Systems 5 (2) 229 (1994)
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Learning in neural network memories

L F Abbott
Network: Computation in Neural Systems 1 (1) 105 (1990)
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Neural network models of list learning

Neil Burgess, J L Shapiro and M A Moore
Network: Computation in Neural Systems 2 (4) 399 (1991)
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Memory maintenance in neural networks

S Shinomoto
Journal of Physics A: Mathematical and General 20 (18) L1305 (1987)
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Categorization in a Hopfield network trained with weighted examples: Extensive number of concepts

Rogério L. Costa and Alba Theumann
Physical Review E 61 (5) 4860 (2000)
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Spin glass model for a neural network : associative memories stored with unequal weights

L. Viana
Journal de Physique 49 (2) 167 (1988)
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Computational modelling of memory retention from synapse to behaviour

Mark C W van Rossum and Maria Shippi
Journal of Statistical Mechanics: Theory and Experiment 2013 (03) P03007 (2013)
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Spin glasses and neural networks

Nestor Parga
Nuclear Physics B - Proceedings Supplements 10 (1) 332 (1989)
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The statistical mechanics of learning a rule

Timothy L. H. Watkin, Albrecht Rau and Michael Biehl
Reviews of Modern Physics 65 (2) 499 (1993)
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A property of neural networks of associative memory with replacing units

Akira Date and Koji Kurata
Artificial Life and Robotics 12 (1-2) 291 (2008)
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Neural network with hierarchical clustering near saturation

M A Pires Idiart and A Theumann
Journal of Physics A: Mathematical and General 25 (4) 779 (1992)
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Hierarchical associative networks

C Cortes, A Krogh and J A Hertz
Journal of Physics A: Mathematical and General 20 (13) 4449 (1987)
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Categorization in a Hopfield network trained with weighted examples. (I). Finite number of concepts

Rogério L. Costa and Alba Theumann
Physica A: Statistical Mechanics and its Applications 268 (3-4) 499 (1999)
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Embedding Responses in Spontaneous Neural Activity Shaped through Sequential Learning

Tomoki Kurikawa, Kunihiko Kaneko and Tim Behrens
PLoS Computational Biology 9 (3) e1002943 (2013)
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Neuronal models of cognitive functions

Jean-Pierre Changeux and Stanislas Dehaene
Cognition 33 (1-2) 63 (1989)
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A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks

Alireza Alemi, Carlo Baldassi, Nicolas Brunel, Riccardo Zecchina and Peter E. Latham
PLOS Computational Biology 11 (8) e1004439 (2015)
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Properties of Hopfield model with the zero-order synaptic decay

Ryota Miyata, Toru Aonishi, Jun Tsuzurugi and Koji Kurata
Artificial Life and Robotics 17 (1) 163 (2012)
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Memory capacity of neural networks learning within bounds

Mirta B. Gordon
Journal de Physique 48 (12) 2053 (1987)
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Neural networks as models of associative memories

N. Parga
Computer Physics Communications 55 (1) 77 (1989)
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Multifractality in forgetful memories

U. Behn, J.L. van Hemmen, R. Kühn, A. Lange and V.A. Zagrebnov
Physica D: Nonlinear Phenomena 68 (3-4) 401 (1993)
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Methods and Models in Neurophysics, École d' été de Physique des Houches Session LXXX

Nicolas Brunel
Les Houches, Methods and Models in Neurophysics, École d' été de Physique des Houches Session LXXX 80 407 (2005)
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Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation

Christian Tetzlaff, Christoph Kolodziejski, Marc Timme, et al.
PLoS Computational Biology 9 (10) e1003307 (2013)
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Dynamics and statistical mechanics of the Hopfield model

A D Bruce, E J Gardner and D J Wallace
Journal of Physics A: Mathematical and General 20 (10) 2909 (1987)
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Forgetting Memories and Their Attractiveness

Enzo Marinari
Neural Computation 31 (3) 503 (2019)
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Stochastic neural networks with the weighted Hebb rule

Caren Marzban and Raju Viswanathan
Physics Letters A 191 (1-2) 127 (1994)
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Neural networks as content addressable memories and learning machines

Roland Köberle
Computer Physics Communications 56 (1) 43 (1989)
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Iterated learning in a layered feed-forward neural network

Ronny Meir and Eytan Domany
Physical Review A 37 (7) 2660 (1988)
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Time scales of memory, learning, and plasticity

Christian Tetzlaff, Christoph Kolodziejski, Irene Markelic and Florentin Wörgötter
Biological Cybernetics 106 (11-12) 715 (2012)
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Self-consistent signal-to-noise analysis of Hopfield model with unit replacement

Toru Aonishi, Yasunao Komatsu and Koji Kurata
Neural Networks 23 (10) 1180 (2010)
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Principal component analysis of the magnetic transition in the three-dimensional Fermi-Hubbard model

Ehsan Khatami
Journal of Physics: Conference Series 1290 (1) 012006 (2019)
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Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data

Ulises Pereira and Nicolas Brunel
Neuron 99 (1) 227 (2018)
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A Short-Term Neural Network Memory

Robert J. T. Morris and Wing Shing Wong
SIAM Journal on Computing 17 (6) 1103 (1988)
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Enhancing the learning of a finite number of patterns in neural networks

J F Fontanari and R Koberle
Journal of Physics A: Mathematical and General 21 (4) L253 (1988)
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Statistical Mechanics of On-Line Learning Under Concept Drift

Michiel Straat, Fthi Abadi, Christina Göpfert, Barbara Hammer and Michael Biehl
Entropy 20 (10) 775 (2018)
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ICANN ’93

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Recall of old and recent information

Vipin Srivastava, Meena Vipin and Enzo Granato
Network: Computation in Neural Systems 9 (2) 159 (1998)
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Storing patterns in a spin-glass model of neural networks nears saturation

D Grensing, R Kuhn and J L van Hemmen
Journal of Physics A: Mathematical and General 20 (10) 2935 (1987)
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Relative stability in the dynamics of a two-pattern neural net

F Pazmandi and T Geszti
Journal of Physics A: Mathematical and General 22 (23) 5117 (1989)
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Effects of temporary synaptic strengthening and residual cell potential in the retrieval of patterns

Tohru Nakano and Osamu Moriyama
Network: Computation in Neural Systems 5 (2) 229 (1994)
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Constraints on learning in dynamic synapses

Daniel Amit and Stefano Fusi
Network: Computation in Neural Systems 3 (4) 443 (1992)
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Neural network models of list learning

Neil Burgess, J Shapiro and M Moore
Network: Computation in Neural Systems 2 (4) 399 (1991)
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Learning in neural network memories

L Abbott
Network: Computation in Neural Systems 1 (1) 105 (1990)
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Selective pattern recall in neural networks by chemical modulation

A C C Coolen and A J Noest
Journal of Physics A: Mathematical and General 23 (4) 575 (1990)
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Unsupervised dynamic learning in layered neural networks

H J J Jonker and A C C Coolen
Journal of Physics A: Mathematical and General 24 (17) 4219 (1991)
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Learning drifting concepts with neural networks

M Biehl and H Schwarze
Journal of Physics A: Mathematical and General 26 (11) 2651 (1993)
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Storing extensively many weighted patterns in a saturated neural network

J L van Hemmen and V A Zagrebnov
Journal of Physics A: Mathematical and General 20 (12) 3989 (1987)
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Optimal storage properties of neural network models

E Gardner and B Derrida
Journal of Physics A: Mathematical and General 21 (1) 271 (1988)
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Content-addressability and learning in neural networks

B M Forrest
Journal of Physics A: Mathematical and General 21 (1) 245 (1988)
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A memory model with novel behaviour in sequential learning

P Kahn, K Wong and D Sherrington
Network: Computation in Neural Systems 6 (3) 415 (1995)
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The space of interactions in neural network models

E Gardner
Journal of Physics A: Mathematical and General 21 (1) 257 (1988)
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A neural network model of working memory exhibiting primacy and recency

K Y M Wong, P E Kahn and D Sherrington
Journal of Physics A: Mathematical and General 24 (5) 1119 (1991)
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Learning and forgetting on asymmetric, diluted neural networks

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Extensions of a solvable feed forward neural network

Ronny Meir
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On-Line Learning of a Time-Dependent Rule

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Statistical Mechanics of Neural Networks

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Article cité par

Article cité :

Solvable models of working memories

Citations de cet article :

Response : Computing with Neural Networks

Inhomogeneities in Heteroassociative Memories with Linear Learning Rules

Layered feed-forward neural network with exactly soluble dynamics

Potts-glass models of neural networks

Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization

Introduction to neural network models

Soft-bound Synaptic Plasticity Increases Storage Capacity

Retrieval Properties of Neural Networks with Infinitely Many Marked Patterns

Paramagnetic unlearning in neural network models

Maximum Storage Capacity in Neural Networks

Information storage in neural networks with low levels of activity

Domain Theory in Learning Processes

Associative Memory for Online Learning in Noisy Environments Using Self-Organizing Incremental Neural Network

Principal component analysis for fermionic critical points

Recall of old and recent information

A memory model with novel behaviour in sequential learning

Constraints on learning in dynamic synapses

Effects of temporary synaptic strengthening and residual cell potential in the retrieval of patterns

Learning in neural network memories

Neural network models of list learning

Memory maintenance in neural networks

Categorization in a Hopfield network trained with weighted examples: Extensive number of concepts

Spin glass model for a neural network : associative memories stored with unequal weights

Computational modelling of memory retention from synapse to behaviour

Spin glasses and neural networks

The statistical mechanics of learning a rule

A property of neural networks of associative memory with replacing units

Neural network with hierarchical clustering near saturation

Hierarchical associative networks

Categorization in a Hopfield network trained with weighted examples. (I). Finite number of concepts

Embedding Responses in Spontaneous Neural Activity Shaped through Sequential Learning

Neuronal models of cognitive functions

A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks

Properties of Hopfield model with the zero-order synaptic decay

Memory capacity of neural networks learning within bounds

Neural networks as models of associative memories

Multifractality in forgetful memories

Methods and Models in Neurophysics, École d' été de Physique des Houches Session LXXX

Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation

Dynamics and statistical mechanics of the Hopfield model

Forgetting Memories and Their Attractiveness

Stochastic neural networks with the weighted Hebb rule

Neural networks as content addressable memories and learning machines

Iterated learning in a layered feed-forward neural network

Time scales of memory, learning, and plasticity

Self-consistent signal-to-noise analysis of Hopfield model with unit replacement

Principal component analysis of the magnetic transition in the three-dimensional Fermi-Hubbard model

Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data

A Short-Term Neural Network Memory

Enhancing the learning of a finite number of patterns in neural networks

Statistical Mechanics of On-Line Learning Under Concept Drift

ICANN ’93

Recall of old and recent information

Storing patterns in a spin-glass model of neural networks nears saturation

Relative stability in the dynamics of a two-pattern neural net

Effects of temporary synaptic strengthening and residual cell potential in the retrieval of patterns

Constraints on learning in dynamic synapses

Neural network models of list learning

Learning in neural network memories

Selective pattern recall in neural networks by chemical modulation

Unsupervised dynamic learning in layered neural networks

Learning drifting concepts with neural networks

Storing extensively many weighted patterns in a saturated neural network

Optimal storage properties of neural network models

Content-addressability and learning in neural networks

A memory model with novel behaviour in sequential learning

The space of interactions in neural network models

A neural network model of working memory exhibiting primacy and recency

Learning and forgetting on asymmetric, diluted neural networks

Nonlinear neural networks. II. Information processing

Information processing in three-state neural networks

Extensions of a solvable feed forward neural network

On-Line Learning of a Time-Dependent Rule

Statistical Mechanics of Neural Networks

Statistical Mechanics of Neural Networks

Glauber dynamics of the Little-Hopfield model