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Published in 2019 at "Quarterly Journal of the Royal Meteorological Society"
DOI: 10.1002/qj.3386
Abstract: This paper studies multiplicative inflation: the complementary scaling of the state covariance in the ensemble Kalman filter (EnKF). Firstly, error sources in the EnKF are catalogued and discussed in relation to inflation; nonlinearity is given…
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Keywords:
kalman filter;
scale;
ensemble kalman;
adaptive inflation ... See more keywords
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Published in 2018 at "Pattern Analysis and Applications"
DOI: 10.1007/s10044-018-0692-5
Abstract: Image denoising is a classical problem in image processing and is known to be closely related to sparse coding. In this work, based on the key observation that the probability density function (PDF) of image…
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Keywords:
image;
scale mixture;
sparse;
image denoising ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3203484
Abstract: Overfitting of neural networks to training data is one of the most significant problems in machine learning. Bayesian neural networks (BNNs) are known to be robust against overfitting owing to their ability to model parameter…
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Keywords:
bayes backprop;
decoupled bayes;
adamb;
gaussian scale ... See more keywords
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Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2023.3265103
Abstract: Image reconstruction from partial observations has attracted increasing attention. Conventional image reconstruction methods with hand-crafted priors often fail to recover fine image details due to the poor representation capability of the hand-crafted priors. Deep learning…
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Keywords:
gaussian scale;
image reconstruction;
image;
scale mixture ... See more keywords