SPDEs bibliography maintained by Le Chen

• SPDEs bibliography maintained by Le Chen
  • Motivation
  • Current Statistics
  • Demo using nvim
  • The bib file: All.bib.
  • Explanations
  • Documentation
  • Some other related tools
  • How to contribute
  • Cite this work?
  • Acknowledgment
  • License

Motivation

When writing a paper, it is not an easy task to keep the bibliography part correct and updated. This process is also very time-consuming. Through this repo, we provide a uniform access to the latest bibliography entries related to the research area of the author: Stochastic Partial Differential Equations (SPDEs) and related fields.

Current Statistics

Demo using nvim

• Similar auto completion function exists in Overleaf.

The bib file: All.bib.

• A GPT model was created to query the database on Nov. 12th 2023. The results are far from being usable, actually a little disappointed, but you can may some fun to play with it. Here is the link.

Explanations

1. Most entries downloaded from MathSciNet to keep the records consistent.
2. The BibTool is used to generate the citation keys.

• The convention is two last names separated with period and two digit for year surrounded by :, and the first word in the title. For example, dalang:99:extending.

3. All references are listed in All.pdf, check All.tex for the usage of biber to handle the bibliography.
4. How entries are selected? Here are some general three principles that have been used:
   1. All papers from some authors whose research interest is close to mine are included.
   2. References from some interesting papers, whenever there is a MR number, are included.
   3. References that we come across will be included.
5. Sample setup using neovim
6. All_Numbered pdf is generated by bib2pdf All.bib All_Numbered.pdf, where the list of references are listed by numbers.
7. More documentation will be added to the wikipage.

Documentation

https://spdes-bib.readthedocs.io/

Some other related tools

1. papis
2. bibtex-tidy

How to contribute

We strive for accuracy and comprehensiveness in this bibliography bank. If you encounter any errors, typos, or issues, or if you would like to suggest additional entries, we warmly welcome your input. Your contributions are invaluable to the enhancement of this resource. Please feel free to open an issue in the repository or reach out directly via email (chenle02@gmail.com) for any such matters. We aim to address all feedback promptly.

Cite this work?

We hope that the resources compiled in this bibliography bank have been supportive in your research endeavors. We are sincerely grateful for any form of acknowledgment you might extend. Should you wish to mention this work, a statement such as the one below could be included in your acknowledgments section or as a footnote:

  The author(s) would like to recognize the contribution of the GitHub
  repository chenle02/SPDEs-Bib curated by Le Chen, which has supported this
  research.

Or, if you prefer to directly cite this repository, please use the following BibTeX entry¹:

• Le Chen (2023) “SPDEs-Bib: A Comprehensive Bibliography of Stochastic Partial Differential Equations and Related Topics”. GitHub & Zenodo. doi: 10.5281/zenodo.10143432.

@misc{chen:23:spdes-bib,
  author        = {Le Chen},
  title         = {{SPDEs-Bib}: A Comprehensive Bibliography of Stochastic Partial Differential Equations and Related Topics},
  month         = {nov},
  year          = {2023},
  publisher     = {GitHub, Zenodo \& Read the Docs},
  journal       = {GitHub repository},
  doi           = {10.5281/zenodo.10143431},
  url           = {https://spdes-bib.readthedocs.io}
}

Your support in recognizing the effort put into compiling and maintaining this repository is much appreciated.

Acknowledgment

I am profoundly grateful to Prof. Edward Dunne, Executive Editor of Mathematical Reviews at the American Mathematical Society, for his invaluable guidance and approval regarding the public availability of this BibTeX file. His willingness to support this initiative, acknowledging the potential benefits to the mathematical community, underscores a deep commitment to enhancing access to mathematical resources.

In our correspondence, Prof. Dunne highlighted the value of using the default tools on MathSciNet (via the subscription), such as MRef and MRLookup. These tools represent the forefront of efforts to facilitate access to comprehensive mathematical reviews and references. I strongly encourage our community to explore and utilize these powerful resources, which can significantly aid in our research and scholarly pursuits.

I extend my sincere thanks to Prof. Dunne for his instrumental support in this project and for reminding us of the importance of continually evolving our tools for the efficient sharing and accessing of mathematical data.

License

CC-BY-SA 4.0

Footnotes

1. To properly show the entry, one may replace misc by book. ↩