Results 51 to 60 of about 9,049,447 (317)
Predictive Coding Strategies for Developmental Neurorobotics
In recent years, predictive coding strategies have been proposed as a possible way of how the brain might make sense of the truly overwhelming amount of sensory data available to the brain at any given moment of time.
Jun-Cheol ePark +3 more
doaj +1 more source
This paper reports on an efficient lossless compression method for periodic signals based on adaptive dictionary predictive coding. Some previous methods for data compression, such as difference pulse coding (DPCM), discrete cosine transform (DCT ...
Shaofei Dai +5 more
doaj +1 more source
On the relationship between predictive coding and backpropagation.
Artificial neural networks are often interpreted as abstract models of biological neuronal networks, but they are typically trained using the biologically unrealistic backpropagation algorithm and its variants.
Robert Rosenbaum
doaj +1 more source
Predictive coding and representationalism [PDF]
According to the predictive coding theory of cognition (PCT), brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled
openaire +4 more sources
Predictive coding of natural images by V1 firing rates and rhythmic synchronization
Summary Predictive coding is an important candidate theory of self-supervised learning in the brain. Its central idea is that sensory responses result from comparisons between bottom-up inputs and contextual predictions, a process in which rates and ...
Cem Uran +9 more
semanticscholar +1 more source
Contextual and Predictive Coding in V1
Primary visual cortex (V1) is often characterized by the receptive field properties of its feed-forward input (only up to 5%). We focussed our fMRI studies on nonstimulated retinotopic regions in V1 to gain a better understanding of contextual processing.
Lars Muckli
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Recurrent predictive coding models for associative memory employing covariance learning
The computational principles adopted by the hippocampus in associative memory (AM) tasks have been one of the mostly studied topics in computational and theoretical neuroscience. Classical models of the hippocampal network assume that AM is performed via
Mufeng Tang +5 more
semanticscholar +1 more source
Multi-view image coding with wavelet lifting and in-band disparity compensation [PDF]
This paper presents a novel framework to achieve scalable multi-view image coding. As open loop operation, the wavelet lifting scheme for geometric filtering has been exploited to overcome the limitation of SNR scalability and to attain view scalability.
Anantrasirichai, N +5 more
core +1 more source
Predictive coding is a consequence of energy efficiency in recurrent neural networks
Predictive coding represents a promising framework for understanding brain function. It postulates that the brain continuously inhibits predictable sensory input, ensuring a preferential processing of surprising elements. A central aspect of this view is
Abdullahi Ali +4 more
semanticscholar +1 more source
Testing the predictive coding account of temporal integration in the human visual system : a computational and behavioural study [PDF]
A major goal of vision science is to understand how the visual system maintains behaviourally relevant perceptions given the level of uncertainty in the signals it receives.
Aitken, Fraser
core +1 more source

