Results 31 to 40 of about 291,981 (317)
Gaussian Process Morphable Models [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018 Statistical shape models (SSMs) represent a class of shapes as a normal distribution of point variations, whose parameters are estimated from example shapes. Principal component analysis (PCA) is applied to obtain a low-dimensional representation of the shape variation in terms of the leading principal components.
Marcel Luthi +3 more
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Manifold Gaussian Processes for regression [PDF]
2016 International Joint Conference on Neural Networks (IJCNN), 2016 26.03.14 KB.
Calandra, R +3 more
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Harmonic State Estimation Method Based on Bayesian Optimized Elastic Network Regression
Zhongguo dianli, 2022 When the regression algorithm is used to estimate the harmonic state of power system, the high correlation between harmonic sources will cause the ill condition of the normal matrix, which will significantly affect the accuracy of harmonic estimation. In
Siqi MA, Zhong WANG
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Science and Technology for Energy TransitionSurrogate models have become a widely used solution for reducing computation times along design processes. In this work, a Gaussian Process surrogate model is built and used to predict the performance and losses of a wound field electrical machine in a ...
Mazloum Rebecca +5 more
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Convolutional Gaussian Processes
, 2017 To appear in Advances in Neural Information Processing Systems 30 (NIPS 2017)
van der Wilk, Mark +2 more
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SCADA based nonparametric models for condition monitoring of a wind turbine
The Journal of Engineering, 2019 High operation and maintenance costs for offshore wind turbines push up the LCOE of offshore wind energy. Unscheduled maintenance due to unanticipated failures is the most prominent driver of the maintenance cost which reinforces the drive towards ...
Ravi Kumar Pandit +2 more
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Model Predictive Controller Design Based on Residual Model Trained by Gaussian Process for Robots
Journal of Marine Science and Engineering, 2023 Model mismatch is inevitable in robot control due to the presence of unknown dynamics and unknown perturbations. Traditional model predictive control algorithms are usually based on constant value assumptions and are not able to overcome the degradation ...
Changjie Wu, Xiaolong Tang, Xiaoyan Xu
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Sparse On-Line Gaussian Processes [PDF]
Neural Computation, 2002 We develop an approach for sparse representations of gaussian process (GP) models (which are Bayesian types of kernel machines) in order to overcome their limitations for large data sets. The method is based on a combination of a Bayesian on-line algorithm, together with a sequential construction of a relevant subsample of the data that fully ...
Csato, Lehel, Opper, Manfred
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Geomatics, Natural Hazards & Risk, 2020 Deformation of surrounding rock is widely monitored to discover surrounding rock behaviors for purpose of event forecasting. This article aims to present a comparative study on surrounding rock nonlinear deformation prediction using computational ...
Peng He, Fei Xu, Shang-qu Sun
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FEBS Letters, EarlyView.Phototrophs evolved light‐harvesting systems adapted for efficient photon capture in habitats enriched in far‐red radiation. A subset of eukaryotic pigment‐binding proteins can absorb far‐red photons via low‐energy chlorophyll states known as red forms.
Antonello Amelii +8 more
wiley +1 more source