Results 51 to 60 of about 942,483 (302)
Geoscience Letters, 2023 Earthquake occurrence modeling of large subduction events involves significant uncertainty, stemming from the scarcity of geological data and inaccuracy of dating techniques.
Katsuichiro Goda
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Denoising With Infinite Mixture Of Gaussians
, 2005 Publication in the conference proceedings of EUSIPCO, Antalya, Turkey ...
Alecu, Teodor +2 more
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Robust Learning of Mixtures of Gaussians [PDF]
, 2021 We resolve one of the major outstanding problems in robust statistics. In particular, if $X$ is an evenly weighted mixture of two arbitrary $d$-dimensional Gaussians, we devise a polynomial time algorithm that given access to samples from $X$ an $\eps$-fraction of which have been adversarially corrupted, learns $X$ to error $\poly(\eps)$ in total ...
openaire +2 more sources
Open, online, interactive visualizations for learning about Gaussian mixture models [PDF]
We construct a website to explain how Gaussian mixture models can be optimized using the expectation maximization algorithm. Previous free, online material on this process has been extremely limited.
Allen, Stuart
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Responsible Gaussian Model: Matrix-Based Approximation of Gaussian Mixture Model
IEEE AccessMechanisms of deep learning are often viewed as a unclear structure and are difficult to interpret or control precisely using mathematical or engineering principles.
Wataru Obayashi +2 more
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Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
FEBS Letters, EarlyView.EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri +5 more
wiley +1 more source
Noise adaptive training for subspace Gaussian mixture models [PDF]
, 2013 Noise adaptive training (NAT) is an effective approach to normalise environmental distortions when training a speech recogniser on noise-corrupted speech.
Renals, Steve, Ghoshal, Arnab, Lu, Liang
core
Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry. [PDF]
PLoS ONE, 2015 Mixture - modeling of mass spectra is an approach with many potential applications including peak detection and quantification, smoothing, de-noising, feature extraction and spectral signal compression.
Andrzej Polanski +4 more
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Emerging experimental and computational methods for studying redox‐regulated structural transitions
FEBS Letters, EarlyView.Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
Nonlinear spectral unmixing of hyperspectral images using Gaussian processes [PDF]
, 2012 This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components ...
Altmann, Yoann +5 more
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