Kathryn Hess, Frédéric Chazal and Umberto Lupo are curating an Article Collection published in Frontiers in Artificial Intelligence and entitled “Topology in Real-World Machine Learning and Data Analysis” (webpage). Its core mission is to promote the use of topological ideas and techniques as mainstream tools in data science.
We welcome contribution(s) to our Article Collection. Papers can be original research, reviews, or perspectives, among other article types. Deadlines are as follows:
- 17 August 2020 – Abstracts (soft deadline);
- 14 December 2020 – Manuscripts.
Upon publications, papers will be free to read for everyone.
There are processing charges associated to publishing with Frontiers in AI, but waivers can be applied for if your institution or grant does not cover Open Access fees.
Please get in touch if you would like to learn more about scope, deadlines, and publishing fees. Alternatively, you can sign up for participation directly from the Collection’s webpage.
Best wishes,Umberto, Kathryn, Frédéric