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The Bayesian Committee Machine (BCM) is an approximation method for
large-scale Gaussian process regression.
- The code is for Matlab
Version 1.0, November 2005-The Bayesian Committee Machine (BCM) is an approximation method for large-scale Gau
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高斯过程在回归和分类问题中的应用，注释详细,Gaussian process regression and classification problems in the application, comments, details
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高斯过程算法在回归和分类中的应用程序。与书本《基于高斯过程的机器学习》配套。本程序是最新的v3.1版，更新于2010-09-27-Gaussian process regression and classification algorithm in the application. And the book " machine learning based on Gaussian process" support. This program is the latest v3.1
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Variational Bayesian Multinomial Probit Regression with
Gaussian Process Priors. -Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors.
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GMM-GMR is a set of Matlab functions to train a Gaussian Mixture Model (GMM) and retrieve generalized data through Gaussian Mixture Regression (GMR). It allows to encode efficiently any dataset in Gaussian Mixture Model (GMM) through the use of an Ex
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GPML的关于GPR gaussian process regression-gaussian process regression GPR
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高斯过程回归算法中计算K矩阵的简单算法，比较简单-Simple algorithm, Gaussian process regression algorithm to calculate the K matrix is relatively simple
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单输出高斯过程回归 代理模型 回归 可代替神经网络-Single output Gaussian process regression
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高斯过程回归算法工具箱，很好用的，我用过-Gaussian process regression algorithm toolbox, well used, I used
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为了提高四足机器人在复杂环境下的适应性,重点研究了采用飞行时间(TOF)原理相机的四足机器人环境感知策略并改进了地形识别及路径规划算法.首先采用高斯过程回归(GPR)模型对TOF相机的距离数据进行误差校正,解决了采用传统多项式或三角函数模型进行误差修正时模型阶次过高及函数组合复杂的问题.基于得到的环境深度信息,采用数字高程模型(DEM)进行地形描述,并通过计算各栅格的坡度、粗糙度、起伏度对地形进行识别.粗糙度由该栅格所处的坡度平面与其8邻域高程点的离散程度进行计算,避免了采用高程方差计算时对粗糙
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高斯过程回归及分类的代码，内容全，有实例，注释清晰。包括分类系列和预测回归系列，值得感兴趣的同学学习借鉴。-Gaussian process regression and classification code, content, there are instances, comments clear.Including classification and forecasting return series, is worthy of reference for anyone interest
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这是一个高斯过程回归和分类工具箱，功能非常齐全，可以为解决高斯过程相关的问题提供很多帮助- GAUSSIAN PROCESS REGRESSION AND CLASSIFICATION Toolbox version 3.6
for GNU Octave 3.2.x and Matlab 7.x
Copyright (c) by Carl Edward Rasmussen and Hannes Nickisch, 2015-07-07.
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利用高斯过程回归建立软测量模型，主程序名为OnlineStage.m,包含数据，可以直接运行，亲测可用。-Gaussian process regression soft sensor model, the main program named OnlineStage.m, contains data that can be run directly, pro-test available.
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高斯过程回归，适用于初学高斯过程回归和分类的同学，有完整的实例与多种辅助函数说明,例如用高斯过程回归进行信道的盲均衡。对于高斯过程回归与分类的进一步学习有很大的帮助。-Gaussian process regression, suitable for beginners gaussian process regression and classification of the classmate, a complete instance and a variety of auxiliary fu
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基于贝叶斯理论的高斯过程代码，包含高斯过程回归分析，以及相关噪声处理和高斯过程分类，提供数据进行测试，-Gauss procedure code based on Bayesian theory, including Gaussian process regression analysis, and related processing and noise Gaussian process classification, to provide data for testing, etc.
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用于高斯过程一维建模，能根据不同的协方差函数得到不同的高斯过程回归模型-For the one-dimensional modeling of the Gaussian process, different Gaussian process regression models can be obtained according to different covariance functions
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Gaussian process regression
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基于高斯过程回归的锂电池充放电性能的预测(Prediction of Charge and Discharge Performance of Lithium Batteries Based on Gaussian Process Regression)
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基于 gpml-matlab-v4.1 工具箱，简单实现了高斯过程回归（Gaussian process regression，GPR）的多变量数据回归，给出了每个预测值的均值以及对应的方差。代码有详细的注释，附有训练数据和测试数据。(Based on the gpml-matlab-v4.1 toolbox, Gaussian process regression (GPR) multivariate data regression is simply implemented, and the
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高斯过程回归是一种基于贝叶斯原理的统计机器学习方法，将先验分布通过贝叶斯定理转化成后验分布，与其他没有采用贝叶斯技巧的预测方法而言，高斯过程最大的优点是能方便地推断出超参数，同时也能方便地给出预测值的置信区间(Gaussian Process Regression is a statistical machine learning method based on Bayesian principle. It transforms prior distribution into posterio
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