Predictive coding equals proximal gradient descent on MAP problems, with priors setting nonlinearities via proximal operators and yielding leaky firing-rate networks plus hierarchical MRFs.
4-Bit ADDER problem
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Bayesian-Hebbian rules achieve the highest capacity for pattern storage and prototype extraction, while additive Hebb performs worst and covariance learning is robust but moderate.
citing papers explorer
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Predictive Coding with Bayesian Priors via Proximal Gradients
Predictive coding equals proximal gradient descent on MAP problems, with priors setting nonlinearities via proximal operators and yielding leaky firing-rate networks plus hierarchical MRFs.
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Benchmarking local Hebbian learning rules for memory storage and prototype extraction
Bayesian-Hebbian rules achieve the highest capacity for pattern storage and prototype extraction, while additive Hebb performs worst and covariance learning is robust but moderate.