Using change-point and Gaussian process models to create baseline energy models in industrial facilities: A comparisonUncertaintyNear-zero energy buildingDegradationLife-cycle performanceDesignNear-zero energy buildings (nZEBs) are considered as an effective solution to mitigating CO2 emissions and reducing ...
change point detection (BOCPD) to increase the generality of the Gaussian process time series methods.These methodologies are evaluated on predictive performance on six real world data sets, which include three environmental data sets, one financial, one biological, and one from industrial well ...
数据划分。如图6和表3所示，基于可见性的相机选择（VisCam）和基于覆盖范围的点选择（CovPoint）都可以...
通过wij的权重来判断第i个gaussian是否是第j个语义标签。 由于3d gaussian 天然的显式的特征(sfm初始化的点云),因此可以直接给这些点赋予语义信息,这样我们就可以在整个编辑过程中可以追溯这些带有明确语义gaussian point。并且在gaussian 致密化的过程中,分裂的儿子节点直接继承父节点的语义,这样就保证在整个训练过程中...
(interaction) kernels much in the same way, conceptually, as with standard linear models. Here we can view the individual kernels as flexible nonlinear functions, which corresponds to the linear terms in linear regression. Plate6was among the first to formulate additive GPs by proposing a sum ...
作者比较了DreamGaussian与现有的优化基和推断式方法在图像到3D任务上的性能,包括与其他优化方法(如Zero-1-to-3和One-2-3-45)和推断方法(如Shap-E和Point-E)的比较。 实验中,作者使用了不同的输入图像,并在生成的3D模型上评估了生成速度和网格质量。
3.1 Gaussian models Assuming a single point source in homogenous and stationary wind and turbulence intensity, the atmospheric transport equation (Eq. (1)) can be solved analytically yielding a normally distributed concentration field (Stockie, 2011). Gaussian (plume) models are based on this analyti...
Collection and interpolation of radiation observations is of vital importance to support routine operations in the nuclear sector globally, as well as for completing surveys during crisis response. To reduce exposure to ionizing radiation that human work
Mdl = fitrgp(Tbl,ResponseVarName) returns a Gaussian process regression (GPR) model trained using the sample data in Tbl, where ResponseVarName is the name of the response variable in Tbl. example Mdl = fitrgp(Tbl,formula) returns a Gaussian process regression (GPR) model, trained using the...
GPflow is a package for building Gaussian process models in Python. It implements modern Gaussian process inference for composable kernels and likelihoods. GPflow builds on TensorFlow 2.4+ and TensorFlow Probability for running computations, which allows fast execution on GPUs. The online documentation ...