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Awesome GitHub RepositoriesKernel Composition
Building complex covariance kernels by combining simpler kernels through mathematical operations.
Distinct from Kernel Composition Frameworks: Distinct from GPU kernel implementation by focusing on the statistical composition of covariance functions.
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Awesome Kernel Composition GitHub Repositories
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- cornellius-gp/gpytorch
cornellius-gp/gpytorch
3,893Ver en GitHubGPyTorch is a GPU-accelerated probabilistic framework and PyTorch library for implementing scalable Gaussian process models. It provides a system for Gaussian process modeling and uncertainty estimation, designed to perform efficient matrix operations on graphics hardware. The framework features a modular kernel system for constructing custom covariance functions and modeling complex data dependencies. It specifically integrates Gaussian processes with deep neural networks to create hybrid models for regression and classification. The system employs numerical linear algebra techniques, inclu
Allows the construction of complex covariance structures by combining simple kernels through addition and multiplication.
Python
