EEG mismatch responses in a multimodal roving stimulus paradigm provide evidence for probabilistic inference across audition, somatosensation, and vision
Sign Up to like & getrecommendations! Published in 2022 at "Human Brain Mapping"
DOI: 10.1002/hbm.26303
Abstract: The human brain is constantly subjected to a multi-modal stream of probabilistic sensory inputs. EEG signatures, such as the mismatch negativity (MMN) and the P3, can give valuable insight into neuronal probabilistic inference. Although reported… read more here.
Keywords: roving stimulus; mismatch responses; cross modal; probabilistic inference ... See more keywords
Robust Least-Squares Support Vector Machine Using Probabilistic Inference.
Sign Up to like & getrecommendations! Published in 2020 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2020.3026680
Abstract: The least-square support vector machine (LS-SVM) has been deeply studied in the machine-learning field and widely applied on a great deal of occasions. A disadvantage is that it is less efficient in dealing with the… read more here.
Keywords: vector machine; probabilistic inference; machine; support vector ... See more keywords
Dynamical Mechanism of Sampling-Based Probabilistic Inference Under Probabilistic Population Codes
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DOI: 10.1162/neco_a_01477
Abstract: Abstract Animals make efficient probabilistic inferences based on uncertain and noisy information from the outside environment. It is known that probabilistic population codes, which have been proposed as a neural basis for encoding probability distributions,… read more here.
Keywords: probabilistic inference; probabilistic population; sampling based; mechanism ... See more keywords
Probabilistic Inference Hybrid IT Value Model Using Bayesian Network
Sign Up to like & getrecommendations! Published in 2020 at "International Journal on Electrical Engineering and Informatics"
DOI: 10.15676/ijeei.2020.12.4.5
Abstract: In this study, we propose probabilistic inference model on a hybrid IT value model using Bayesian Network (BN) that represents uncertain relationships between 13 variables of the model. Those variables are performance, market, innovation, IT… read more here.
Keywords: bayesian network; probabilistic inference; hybrid value; value model ... See more keywords
Probabilistic Inference with Polymerizing Biochemical Circuits
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DOI: 10.3390/e24050629
Abstract: Probabilistic inference—the process of estimating the values of unobserved variables in probabilistic models—has been used to describe various cognitive phenomena related to learning and memory. While the study of biological realizations of inference has focused… read more here.
Keywords: biochemical circuits; probabilistic inference; polymerizing biochemical; inference polymerizing ... See more keywords