https://github.com/aaltoml/t-svgp
Codes for 'Dual Parameterization of Sparse Variational Gaussian Processes' (NeurIPS 2021)
Science Score: 10.0%
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✓Academic publication links
Links to: arxiv.org -
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○Scientific vocabulary similarity
Low similarity (12.9%) to scientific vocabulary
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Repository
Codes for 'Dual Parameterization of Sparse Variational Gaussian Processes' (NeurIPS 2021)
Basic Info
Statistics
- Stars: 7
- Watchers: 1
- Forks: 1
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
Dual Parameterization of Sparse Variational Gaussian Processes
Documentation | Notebooks | API reference
Introduction
This repository is the official implementation of the methods in the publication:
- V. Adam, P.E. Chang, M.E. Khan, and A. Solin (2021). Dual Parameterization of Sparse Variational Gaussian Processes. In Advances in Neural Information Processing Systems (NeurIPS). [arXiv]
The paper's main result shows that an alternative (dual) parameterization for SVGP models leads to a better objective for learning and allows for faster inference via natural gradient descent.
Repository structure
The repository has the following folder structure:
scrcontains the source codeexperimentscontains scripts to reproduce some of the experiments presented in the paperdocscontains documentation in the form of notebooks and an api reference.testscontains unit and integration tests for the source code
Installation
We recommend using Python version 3.7.3 and pip version 20.1.1. To install the package, run:
bash
pip install -e .
To run the tests, notebooks, build the docs or run the experiments, install the dependencies:
bash
pip install \
-r tests_requirements.txt \
-r notebook_requirements.txt \
-r docs/docs_requirements.txt \
-e .
Notebooks
To build the notebooks from source, use jupytext:
bash
jupytext --to notebook [filename].py
Citation
If you use the code in this repository for your research, please cite the paper as follows:
bibtex
@inproceedings{adam2021dual,
title={Dual Parameterization of Sparse Variational {G}aussian Processes},
author={Adam, Vincent and Chang, Paul Edmund and Khan, Mohammad Emtiyaz and Solin, Arno},
booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
year={2021}
}
Contributing
For all correspondence, please contact vincenta@gatsby.ucl.ac.uk.
License
This software is provided under the MIT license.
Owner
- Name: AaltoML
- Login: AaltoML
- Kind: organization
- Location: Finland
- Website: http://arno.solin.fi
- Repositories: 20
- Profile: https://github.com/AaltoML
Machine learning group at Aalto University lead by Prof. Solin
GitHub Events
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- Watch event: 2
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- Watch event: 2
Dependencies
- ipython *
- jupytext *
- nbsphinx *
- pandoc *
- pydata-sphinx-theme *
- sphinx *
- sphinx-autoapi *
- sphinxcontrib-bibtex *
- matplotlib *
- pandas *
- scikit-learn *
- jupyter *
- matplotlib *
- pandas *
- scikit-learn *
- black ==20.8b1 test
- codecov * test
- flake8 ==3.8.4 test
- ipykernel * test
- isort ==5.6.4 test
- jupyter_client * test
- jupytext * test
- mypy ==0.770 test
- nbconvert * test
- nbformat * test
- pytest * test
- pytest-cov * test
- pytest-mock * test
- pytest-random-order * test
- tornado * test
- tqdm * test