Essays about: "Bayesian Confidence Propagating Neural Networks"

Found 3 essays containing the words Bayesian Confidence Propagating Neural Networks.

  1. 1. Regression with Bayesian Confidence Propagating Neural Networks

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Raghav Rajendran Bongole; [2023]
    Keywords : Machine Learning; Neural Networks; Brain-like computing; Bayesian Confidence Propagating Neural Networks; Maskininlärning; neurala nätverk; hjärnliknande datorer; Bayesian Förtroendespridande neurala nätverk;

    Abstract : Bayesian Confidence Propagating Neural Networks (BCPNNs) are biologically inspired artificial neural networks. These networks have been modeled to account for brain-like aspects such as modular architecture, divisive normalization, sparse connectivity, and Hebbian learning. READ MORE

  3. 2. Effects of Network Size in a Recurrent Bayesian Confidence Propagating Neural Network With two Synaptic Traces

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : William Laius Lundgren; Ludwig Karlsson; [2021]
    Keywords : BCPNN; computational brain modelling; shortterm memory; sequential learning; hypercolumns;

    Abstract : A modular Recurrent Bayesian Confidence PropagatingNeural Networks (BCPNN) with two synaptic time tracesis a computational neural network that can serve as a modelof biological short term memory. The units in the network aregrouped into modules called hypercolumns within which there isa competitive winner-takes-all mechanism. READ MORE

  4. 3. Modelling Immediate Serial Recall using a Bayesian Attractor Neural Network

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Julia Ericson; [2021]
    Keywords : Bayesian Confidence Propagating Neural Network; Phonological Loop; Computational model; Immediate serial recall; Bayesian Confidence Propagating Neural Network; Fonologiska loopen; Datorsimulation; Sekventiellt korttidsminne;

    Abstract : In the last decades, computational models have become useful tools for studying biological neural networks. These models are typically constrained by either behavioural data from neuropsychological studies or by biological data from neuroscience. READ MORE