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Martingale approach to neural networks with hierarchically structured information
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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/bf01304440openalex-snapshot
Learning and pattern recognition in spin glass models
inferredcites →https://doi.org/10.1007/bf01323440openalex-snapshot
Learning and pattern recognition in spin glass models
inferredcites →https://doi.org/10.1016/0370-1573(80)90095-2openalex-snapshot
Dynamics and ergodicity of the infinite harmonic crystal
inferredcites →https://doi.org/10.1016/c2009-0-22097-6openalex-snapshot
A Course in Probability Theory
inferredcites →https://doi.org/10.1051/jphys:0198600470110185700openalex-snapshot
The ultrametric organization of memories in a neural network
inferredcites →https://doi.org/10.1051/jphyslet:019850046014062300openalex-snapshot
Scaling laws for the attractors of Hopfield networks
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/10.1088/0022-3719/18/31/008openalex-snapshot
'Ordered' spin glass: a hierarchical memory machine
inferredcites →https://doi.org/10.1088/0305-4470/12/4/016openalex-snapshot
The replica method and solvable spin glass model
inferredcites →https://doi.org/10.1088/0305-4470/20/10/036openalex-snapshot
Storing patterns in a spin-glass model of neural networks nears saturation
inferredcites →https://doi.org/10.1088/0305-4470/20/12/043openalex-snapshot
Storing extensively many weighted patterns in a saturated neural network
inferredcites →https://doi.org/10.1088/0305-4470/20/13/044openalex-snapshot
Hierarchical associative networks
inferredcites →https://doi.org/10.1103/physreva.36.1959openalex-snapshot
Nonlinear neural networks near saturation
inferredcites →https://doi.org/10.1103/physrevlett.55.1530openalex-snapshot
Storing Infinite Numbers of Patterns in a Spin-Glass Model of Neural Networks
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-1-4471-0509-1_13openalex-snapshot
Neural Networks with Hierarchically Structured Information and its Unlearning Effects
inferred← citeshttps://doi.org/10.1007/978-3-642-79814-6_1openalex-snapshot
Collective Phenomena in Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-642-79814-6_5openalex-snapshot
Hierarchical Organization of Memory
inferred← citeshttps://doi.org/10.1007/978-3-642-97171-6_1openalex-snapshot
Collective Phenomena in Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-642-97171-6_5openalex-snapshot
Hierarchical Organization of Memory
inferred← citeshttps://doi.org/10.1007/bf01313576openalex-snapshot
Neural networks with low levels of activity: Ising vs. McCulloch-Pitts neurons
inferred← citeshttps://doi.org/10.1007/bf01321917openalex-snapshot
Transients and basins of attraction in neutral network models
inferred← citeshttps://doi.org/10.1007/bf01437658openalex-snapshot
On learning and recognition of temporal sequences of correlated patterns
inferred← citeshttps://doi.org/10.1016/0378-4371(90)90345-sopenalex-snapshot
Increasing the efficiency of a neural network through unlearning
inferred← citeshttps://doi.org/10.1016/j.physa.2024.129512openalex-snapshot
Statistical mechanics of learning via reverberation in bidirectional associative memories
inferred← citeshttps://doi.org/10.1016/s0893-6080(02)00239-3openalex-snapshot
Two-level hierarchy with sparsely and temporally coded patterns and its possible functional role in information processing
inferred← citeshttps://doi.org/10.1088/0305-4470/22/21/012openalex-snapshot
Increased storage capacity for hierarchically structured information in a neural network of Ising type
inferred← citeshttps://doi.org/10.1088/0305-4470/23/12/034openalex-snapshot
Storage of hierarchically correlated patterns
inferred← citeshttps://doi.org/10.1088/0305-4470/23/6/009openalex-snapshot
Storage capacity for hierarchically correlated patterns
inferred← citeshttps://doi.org/10.1088/0954-898x/2/1/004openalex-snapshot
Recognition and categorization in a structured neural network with attractor dynamics
inferred← citeshttps://doi.org/10.1088/1751-8121/aa89a2openalex-snapshot
Cell reprogramming modelled as transitions in a hierarchy of cell cycles
inferred← citeshttps://doi.org/10.1103/physreva.45.4194openalex-snapshot
Thermodynamic properties of theQ-state Potts-glass neural network
inferred← citeshttps://doi.org/10.1103/physreve.52.870openalex-snapshot
Hierarchically correlated patterns in Potts neural networks
inferred← citeshttps://doi.org/10.1103/physreve.53.1276openalex-snapshot
Learning rules for Potts neural networks with biased patterns
inferred← citeshttps://doi.org/10.1103/physreve.56.7306openalex-snapshot
Categorization by a three-state attractor neural network
inferred← citeshttps://doi.org/10.1109/72.641470openalex-snapshot
On the problem of spurious patterns in neural associative memory models
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1009691openalex-snapshot
When shared concept cells support associations: Theory of overlapping memory engrams
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