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Nonlinear neural networks. I. General theory
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-642-96483-1openalex-snapshot
Monte Carlo Methods in Statistical Physics
inferredcites →https://doi.org/10.1007/bf00317939openalex-snapshot
Collective properties of neural networks: A statistical physics approach
inferredcites →https://doi.org/10.1007/bf00339943openalex-snapshot
“Neural” computation of decisions in optimization problems
inferredcites →https://doi.org/10.1007/bf01304440openalex-snapshot
Learning and pattern recognition in spin glass models
inferredcites →https://doi.org/10.1007/bf01308399openalex-snapshot
Elementary solution of Classical Spin-Glass models
inferredcites →https://doi.org/10.1007/bf02478259openalex-snapshot
A logical calculus of the ideas immanent in nervous activity
inferredcites →https://doi.org/10.1016/0025-5564(74)90031-5openalex-snapshot
The existence of persistent states in the brain
inferredcites →https://doi.org/10.1016/s0361-9230(99)00182-3openalex-snapshot
D.O. Hebb: The Organization of Behavior, Wiley: New York; 1949
inferredcites →https://doi.org/10.1063/1.3127900openalex-snapshot
Introduction to Phase Transitions and Critical Phenomena
inferredcites →https://doi.org/10.1073/pnas.79.8.2554openalex-snapshot
Neural networks and physical systems with emergent collective computational abilities.
inferredcites →https://doi.org/10.1073/pnas.83.6.1695openalex-snapshot
Spin glass model of learning by selection.
inferredcites →https://doi.org/10.1088/0305-4470/19/18/007openalex-snapshot
Random-site spin-glass models
inferredcites →https://doi.org/10.1103/physrev.149.301openalex-snapshot
Relaxation Times for Metastable States in the Mean-Field Model of a Ferromagnet
inferredcites →https://doi.org/10.1103/physreva.29.355openalex-snapshot
Statistical-mechanical formalism for spin-glasses
inferredcites →https://doi.org/10.1103/physreva.32.1007openalex-snapshot
Spin-glass models of neural networks
inferredcites →https://doi.org/10.1103/physreva.34.2509openalex-snapshot
Chopper model of pattern recognition
inferredcites →https://doi.org/10.1103/physreva.34.2571openalex-snapshot
Neural networks with nonlinear synapses and a static noise
inferredcites →https://doi.org/10.1103/physreva.34.3435openalex-snapshot
Spin-glass models of a neural network
inferredcites →https://doi.org/10.1103/physrevlett.49.409openalex-snapshot
Classical Spin-Glass Model
inferredcites →https://doi.org/10.1103/physrevlett.55.1530openalex-snapshot
Storing Infinite Numbers of Patterns in a Spin-Glass Model of Neural Networks
inferredcites →https://doi.org/10.1119/1.1986710openalex-snapshot
Introduction to Phase Transitions and Critical Phenomena
inferredcites →https://doi.org/10.1209/0295-5075/1/10/008openalex-snapshot
Networks of Formal Neurons and Memory Palimpsests
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/3-540-58843-4_15openalex-snapshot
Neural coding: A theoretical vista of mechanisms, techniques, and applications
inferred← citeshttps://doi.org/10.1007/978-1-4612-4320-5_1openalex-snapshot
Coding and Information Processing in Neural Networks
inferred← citeshttps://doi.org/10.1007/978-1-4612-4320-5_5openalex-snapshot
Associative Binding and Segregation in a Network of Spiking Neurons
inferred← citeshttps://doi.org/10.1007/978-3-642-79814-6_1openalex-snapshot
Collective Phenomena in Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-642-97171-6_1openalex-snapshot
Collective Phenomena in Neural Networks
inferred← citeshttps://doi.org/10.1007/978-94-017-1323-8_3openalex-snapshot
Thermodynamic Formalism of Neural Computing
inferred← citeshttps://doi.org/10.1007/bf00201861openalex-snapshot
A biologically motivated and analytically soluble model of collective oscillations in the cortex
inferred← citeshttps://doi.org/10.1007/bf00204701openalex-snapshot
Hebbian learning reconsidered: Representation of static and dynamic objects in associative neural nets
inferred← citeshttps://doi.org/10.1007/bf01041070openalex-snapshot
Information processing in three-state neural networks
inferred← citeshttps://doi.org/10.1007/bf01041071openalex-snapshot
Some rigorous results on the Hopfield neural network model
inferred← citeshttps://doi.org/10.1007/bf01406600openalex-snapshot
Dynamical equivalence in a class of nonlinear neural network models
inferred← citeshttps://doi.org/10.1007/bf01413707openalex-snapshot
A neural network model of a communication network with information servers
inferred← citeshttps://doi.org/10.1016/0167-2789(93)90133-lopenalex-snapshot
Multifractality in forgetful memories
inferred← citeshttps://doi.org/10.1016/j.neuron.2025.12.047openalex-snapshot
Linking neural manifolds to circuit structure in recurrent networks
inferred← citeshttps://doi.org/10.1016/s0375-9601(00)00042-6openalex-snapshot
Two theorems on pseudo-spin of Hubbard models
inferred← citeshttps://doi.org/10.1016/s1571-0661(04)80007-0openalex-snapshot
Domain Theory in Learning Processes
inferred← citeshttps://doi.org/10.1017/s0001867800026744openalex-snapshot
A limit theorem for certain disordered random systems
inferred← citeshttps://doi.org/10.1063/1.529474openalex-snapshot
A scaling limit of the Glauber dynamics for a class of neural network models
inferred← citeshttps://doi.org/10.1088/0305-4470/22/15/026openalex-snapshot
Complex temporal association in neural networks
inferred← citeshttps://doi.org/10.1088/0954-898x/3/2/004openalex-snapshot
Associative memory in a network of ‘spiking’ neurons
inferred← citeshttps://doi.org/10.1088/0954-898x/4/2/005openalex-snapshot
Associative memory for patterns with different bias
inferred← citeshttps://doi.org/10.1103/physrevb.45.3145openalex-snapshot
Rigorous theorems on off-diagonal long-range order in the negative-UHubbard model
inferred← citeshttps://doi.org/10.1103/physrevb.50.16086openalex-snapshot
Relation between pseudospin-rotation invariance and a supersolid
inferred← citeshttps://doi.org/10.1103/physreve.51.738openalex-snapshot
Time structure of the activity in neural network models
inferred← citeshttps://doi.org/10.1103/physreve.52.6593openalex-snapshot
Role of noises in neural networks
inferred← citeshttps://doi.org/10.1103/physreve.55.5849openalex-snapshot
Stimulus-dependent correlations in stochastic networks
inferred← citeshttps://doi.org/10.1103/physreve.57.2095openalex-snapshot
Random and systematic dilutions of synaptic connections in a neural network with a nonmonotonic response function
inferred← citeshttps://doi.org/10.1103/physrevlett.134.018401openalex-snapshot
Emergent Rate-Based Dynamics in Duplicate-Free Populations of Spiking Neurons
inferred← citeshttps://doi.org/10.1103/revmodphys.65.499openalex-snapshot
The statistical mechanics of learning a rule
inferred← citeshttps://doi.org/10.1109/ijcnn.1989.118557openalex-snapshot
A collective computation approach to automatic target recognition
inferred← citeshttps://doi.org/10.1209/0295-5075/7/7/016openalex-snapshot
The Hebb Rule: Storing Static and Dynamic Objects in an Associative Neural Network
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