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gpflow
Here are 16 public repositories matching this topic...
Bayesian Optimization using GPflow
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Dec 2, 2020 - Python
Deep convolutional gaussian processes.
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Sep 4, 2019 - Jupyter Notebook
Non-stationary spectral mixture kernels implemented in GPflow
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Nov 30, 2018 - Python
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Mar 18, 2021 - Python
Gaussian-Processes Surrogate Optimisation in python
neuroscience
python3
gaussian-processes
optimisation
neuroscience-methods
bayesian-optimisation
gpflow
space-partition-tree
gaussian-processes-surrogate
scale-biophysical-models
partition-tree
brainweb
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May 18, 2021 - Python
Library for Deep Gaussian Processes based on GPflow
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Mar 31, 2020 - Python
Interactive Gaussian Processes
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Jul 19, 2019 - Jupyter Notebook
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Jun 16, 2020 - Python
Sparse Heteroscedastic Gaussian Processes
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Oct 8, 2021 - Python
Subset of Data Variational Inference for Deep Gaussian Process Model
tensorflow
probabilistic-programming
deeplearning
bayesian-inference
variational-inference
probabilistic-graphical-models
gpflow
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Sep 29, 2021 - Python
Implementation of the COGP model
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Dec 31, 2017 - Jupyter Notebook
Implements AT-GP from Cao et. al. 2010 in GPflow
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Jul 24, 2018 - Python
Gaussian processes in TensorFlow
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Aug 7, 2017 - Python
Towards GPflow 1.0
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Sep 21, 2017 - HTML
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Jul 8, 2021 - Jupyter Notebook
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Feature request
In several places we use multiple dispatch. Right now the types to dispatch on are configured separately. Could we infer the types to dispatch on from Python type hints? That would simplify the code.
Motivation
Instead of: