tmlr-biblatex-proposal
Science Score: 18.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (4.0%) to scientific vocabulary
Last synced: 10 months ago
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Repository
Basic Info
- Host: GitHub
- Owner: aterenin
- Language: TeX
- Default Branch: main
- Size: 2.93 KB
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Created over 2 years ago
· Last pushed over 2 years ago
Metadata Files
Readme
Citation
README.md
TMLR BibLaTeX proposal
This repository contains proposed LaTeX code to be added to the TMLR style file, which switches it from natbib to the much newer biblatex reference management system.
It also contains a test document which can be compiled to check behavior of edge cases, such as for instance when the same author has multiple papers of the same year.
A compiled version of the test document is available here.
Owner
- Name: Alexander Terenin
- Login: aterenin
- Kind: user
- Website: https://avt.im/
- Twitter: avt_im
- Repositories: 6
- Profile: https://github.com/aterenin
Postdoc - Machine Intelligence - University of Cambridge
Citation (citation_tests.bib)
%% This BibTeX bibliography file was created using BibDesk.
%% https://bibdesk.sourceforge.io/
%% Created for Alexander Terenin at 2023-10-07 20:57:49 -0400
%% Saved with string encoding Unicode (UTF-8)
@article{wilson21,
author = {James T. Wilson and Viacheslav Borovitskiy and Alexander Terenin and Peter Mostowsky and Marc Peter Deisenroth},
date-added = {2023-10-07 20:51:47 -0400},
date-modified = {2023-10-07 20:51:48 -0400},
journal = {Journal of Machine Learning Research},
number = {105},
pages = {1--47},
title = {Pathwise Conditioning of Gaussian Processes},
volume = {22},
year = {2021},
bdsk-file-1 = {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}}
@inproceedings{wilson20,
author = {James T. Wilson and Viacheslav Borovitskiy and Alexander Terenin and Peter Mostowsky and Marc Peter Deisenroth},
booktitle = {International Conference on Machine Learning},
date-added = {2023-10-07 20:51:47 -0400},
date-modified = {2023-10-07 20:51:48 -0400},
pages = {10292--10302},
title = {Efficiently Sampling Functions from Gaussian Process Posteriors},
year = {2020},
bdsk-file-1 = {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}}
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