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Found 4 papers, 1 papers with code
Bayesian Active Learning for Classification and Preference Learning
Information theoretic active learning has been widely studied for probabilistic models.
Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories
Storing a new pattern in a palimpsest memory system comes at the cost of interfering with the memory traces of previously stored items.
Active dendrites: adaptation to spike-based communication
Computational analyses of dendritic computations often assume stationary inputs to neurons, ignoring the pulsatile nature of spike-based communication between neurons and the moment-to-moment fluctuations caused by such spiking inputs.
Know Thy Neighbour: A Normative Theory of Synaptic Depression
Synapses exhibit an extraordinary degree of short-term malleability, with release probabilities and effective synaptic strengths changing markedly over multiple timescales.
