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Barcode activity in a recurrent network model of the hippocampus enables efficient memory binding. [PDF]
ElifeFang C +4 more
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Colorectal cancer as a complex adaptive system: integrating the hallmarks of cancer with complexity theory. [PDF]
Front OncolBasbus LR.
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Diverse perceptual biases emerge from Hebbian plasticity in a recurrent neural network model.
NeuronSchönsberg F +4 more
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Efficient Working Memory Maintenance via High-Dimensional Rotational Dynamics
Ritter L, Chadwick A.
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Neural Computation, 2001
Attractor networks, which map an input space to a discrete output space, are useful for pattern completion—cleaning up noisy or missing input features. However, designing a net to have a given set of attractors is notoriously tricky; training procedures are CPU intensive and often produce spurious attractors and ill-conditioned attractor basins.
Zemel, Richard S., Mozer, Michael C.
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Attractor networks, which map an input space to a discrete output space, are useful for pattern completion—cleaning up noisy or missing input features. However, designing a net to have a given set of attractors is notoriously tricky; training procedures are CPU intensive and often produce spurious attractors and ill-conditioned attractor basins.
Zemel, Richard S., Mozer, Michael C.
openaire +2 more sources