Revision 48270681afc13081094f7f398a1e194c6b07ba9b authored by vdutor on 03 January 2018, 17:44:53 UTC, committed by Mark van der Wilk on 03 January 2018, 17:44:53 UTC
* Outline of new expectations code. * Quadrature code now uses TensorFlow shape inference. * General expectations work. * Expectations RBF kern, not tested * Add Identity mean function * General unittests for Expectations * Add multipledispatch package to travis * Update tests_expectations * Expectations of mean functions * Mean function uncertain conditional * Uncertain conditional with mean_function. Tested. * Support for Add and Prod kernels and quadrature fallback decorator * Refactor expectations unittests * Psi stats Linear kernel * Split expectations in different files * Expectation Linear kernel and Linear mean function * Remove None's from expectations api * Removed old ekernels framework * Add multipledispatch to setup file * Work on PR feedback, not finished * Addressed PR feedback * Support for pairwise xKxz * Enable expectations unittests * Renamed `TimeseriesGaussian` to `MarkovGaussian` and added tests. * Rename some variable, plus note for later test of <x Kxz>_q. * Update conditionals.py Add comment * Change order of inputs to (feat, kern) * Stef/expectations (#601) * adding gaussmarkov quad * don't override the markvogaussian in the quadrature * can't test * adding external test * quadrature code done and works for MarkovGauss * MarkovGaussian with quad implemented. All tests pass * Shape comments. * Removed superfluous autoflow functions for kernel expectations * Update kernels.py * Update quadrature.py
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roadmap.md
This document covers major planned development items for GPflow.
# Computational speed
- Add further benchmarks to [benchmark repository](https://github.com/GPflow/GPflowBenchmarks) including multiple GPUs.
- Incorporate remaining Tom Nickson GPU code from [branch](https://github.com/c0g/tomserflow) into TensorFlow main.
# Features
- Add ability to exploit Kronecker structure.
# Housekeeping
- See also issues marked "enhancement" in the GitHub [list](https://github.com/GPflow/GPflow/issues).
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