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27 April 2022, 07:49:56 UTC
Revision 1851e0d03aeb50009765fbc73ddb281dc12f70c9 authored by st-- on 27 June 2018, 11:19:26 UTC, committed by Mark van der Wilk on 27 June 2018, 11:19:26 UTC 
Monte-Carlo likelihoods (#799)
 
* add @markvdw's stochastic likelihood, including the softmax

* initial MC likelihood

* remove MonteCarloLikelihood base class from tests

* fix test

* var of predict_mean_and_var and predict_density for MC likelihood

* factor out MC sampling

* add comment for variance bias

* add tests

* fixes

* use same integration as for GH quadrature in MonteCarloLikelihood.predict_mean_and_var()

* .

* increase rtol

* move to proper use of super()

* move MC integration to quadrature module, similar to ndiagquad

* seed to make test deterministic

* add Assert for shape of Y

* tidy up studentT likelihood

* fix for heteroskedastic likelihoods -- requires logp to always call the Y argument Y

* fix doc

* add assert and equivalence tests for SoftMax

* remove erroneously added file

* rename "probit" to inv_probit (which is what it actually is)

* add assert for num_classes to SoftMax

* fix whitespace

* Update RELEASE.md

* Update RELEASE.md
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Tip revision: 1851e0d03aeb50009765fbc73ddb281dc12f70c9 authored by st-- on 27 June 2018, 11:19:26 UTC
Monte-Carlo likelihoods (#799)
Tip revision: 1851e0d
Dockerfile 
# Copyright 2016 The GPflow authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

#USAGE:
#To run from prebuilt version use:
#docker run -it -p 8888:8888 gpflow/gpflow

#To replicate build use:
#docker build -t gpflow/gpflow .
#Assumes you are running from within cloned repo.

#Uses official Tensorflow docker for cpu only.
FROM tensorflow/tensorflow:1.0.0
COPY ./ /usr/local/GPflow/
RUN cd /usr/local/GPflow && \
    python setup.py develop && \
    rm /notebooks/*  && \
    apt-get clean  && \
    rm -rf /var/lib/apt/lists/*
COPY doc/source/notebooks/ LICENSE README.md /notebooks/
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