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27 November 2021, 02:00:58 UTC
Revision 77be468c95e06730f613726ec7a09b9594602b46 authored by John Bradshaw on 10 October 2017, 10:53:08 UTC, committed by John Bradshaw on 10 October 2017, 10:53:08 UTC 
Binary classification with EP
 
* fixed a bug in log likelihood that was causing NaNs
* fixed the gradients for likelihood as was doing too many tf.stop_gradients
* added the option to not rerun EP each time you call log_likelihood
* tidied up the demo so that get nice clean comparison between VGP and EP
* soem numerical fixes and minor refactoring of EP code.
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Tip revision: 77be468c95e06730f613726ec7a09b9594602b46 authored by John Bradshaw on 10 October 2017, 10:53:08 UTC
Binary classification with EP
Tip revision: 77be468
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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