Gaussian approximation [kasetvideo]

Gaussian approximation [kasetvideo]

20

書目詳細資料
格式:
出版:	Cambridge, Mass. : MIT, 1969
主題:	Gaussian processes

相似書籍

Gaussian approximation [filem]
出版: (1969)

Gaussian basis sets for molecular calculations /
由: Huzinaga, S.
出版: (1984)

Conditional expectation [kasetvideo]
出版: (1969)

Correlated non-gaussian sequences and point processes /
由: 407549 Sim, Chiaw Hock
出版: ([19-)

A convergence theorem for extreme values from Gaussian sequences,
由: Welsch, Roy E.
出版: (2009)

Gaussian processes, function theory and the inverse problem /
由: Dym, H. (Harry), 1938-, et al.
出版: (1976)

Conditional expectation [filem]
出版: (1969)

Model-based decision support with uncertain human-centric data
由: Downing, JM
出版: (2019)

The general point process /
由: 406895 Murthy, V. K.
出版: (1974)

Markov processes, gaussian processes and local times /
由: 288432 Marcus, Michael B., et al.
出版: (2006)

Gaussian Distribution Approximation for Localized Effects of Input Parameters
由: Rzepniewski, Adam K., et al.
出版: (2003)

Frozen gaussian approximation for 3D seismic tomography
由: Chai, Lihui, et al.
出版: (2019)

Gaussian measures in Banach Spaces /
由: 241052 Kuo, Hui-Hsiung
出版: (1975)

Modulating scalable Gaussian processes for expressive statistical learning
由: Liu, Haitao, et al.
出版: (2022)

MAP approximation to the variational Bayes Gaussian mixture model and application
由: Lim, Kart-Leong, et al.
出版: (2020)

The performance of expectation maximization (EM) algorithm in Gaussian Mixed Models (GMM)
由: Mohd Yusoff, Mohd Izhan, et al.
出版: (2009)

Probability distributions involving Gaussian random variables : a handbook for engineers and scientists /
由: Simon, Marvin Kenneth, 1939-
出版: (2002)

Gaussian processes on graphs
由: Zhi, Y-C
出版: (2024)

Discriminative Gaussian Process Latent Variable Model for Classification
由: Urtasun, Raquel, et al.
出版: (2007)

The geometry of random fields /
由: 407183 Adler, Robert J.
出版: (1981)

Binary spatial random field reconstruction from non-Gaussian inhomogeneous time-series observations
由: Sheng, Shunan, et al.
出版: (2024)

Understanding and comparing scalable Gaussian process regression for big data
由: Liu, Haitao, et al.
出版: (2020)

Predicting shear strength of corroded RC columns: a probabilistic model with enhanced Gaussian Process Regression
由: Yu, Bo, et al.
出版: (2025)

Bayesian Nonparametric Adaptive Control using Gaussian Processes
由: Chowdhary, Girish, et al.
出版: (2013)

Mechanisms for the emergence of Gaussian correlations
由: Gluza, Marek, et al.
出版: (2023)

Modeling approximately normal distributions with s-systems /
由: 224279 Rust, Philip F.

Probabilistic uncertainty quantification for structural dynamics under limited data
由: Igea, F
出版: (2023)

Learning probabilistic representations for inference, training and interpretability
由: Abbati, G
出版: (2020)

Applied parameter estimation for chemical engineers /
由: 427951 Englezos, Peter, et al.
出版: (2001)

Learning Sparse Gaussian Graphical Model with l0-regularization
由: Mu, Beipeng, et al.
出版: (2014)

Real-time unstable approach detection using sparse variational Gaussian process
由: Singh, Narendra Pratap, et al.
出版: (2020)

When Gaussian process meets big data : a review of scalable GPs
由: Liu, Haitao, et al.
出版: (2021)

Remarks on multi-output Gaussian process regression
由: Liu, Haitao, et al.
出版: (2020)

Non-parametric probabilistic load flow using Gaussian process learning
由: Pareek, Parikshit, et al.
出版: (2021)

Handbook of the normal distribution /
由: 395936 Patel, Jagdish K., et al.
出版: (1982)

Low-Complexity Iterative Row-Column Soft Decision Feedback Algorithm for 2-D Inter-Symbol Interference Channel Detection With Gaussian Approximation
由: Zheng, Jianping, et al.
出版: (2016)

Cope with diverse data structures in multi-fidelity modeling : a Gaussian process method
由: Liu, Haitao, et al.
出版: (2020)

Supplementary material for nonparameteric adaptive control of time varying systems using gaussian processes
由: Chowdhary, Girish, et al.
出版: (2013)

Collusion-resistant spatial phenomena crowdsourcing via mixture of Gaussian Processes regression
由: Zhang, Jie, et al.
出版: (2019)

A new robust dynamic state estimation approach for power systems with non-Gaussian noise
由: Chen, Tengpeng, et al.
出版: (2024)