weakmath @weakmath@algebra.chat

I am happy to share that our paper on the «#Intrinsic #Dimension for Large-Scale Geometric Learning» was published today at #TMLR (https://openreview.net/pdf?id=85BfDdYMBY)

Good bye ...

At the end of the day at #dagstuhl ... a lot of work and a lot of fun...

... and what is more: #Dagstuhl has a very informative #Welcome #Video now... much appreciated.

What an honor to start the #Dagstuhl year 2023 with our meeting on the combination of concept lattices and topological data analysis: https://www.dagstuhl.de/de/seminars/seminar-calendar/seminar-details/23013

What comes next? Apart from adding more research fields, we will add #higher #resolution topic models and integrate the possibility to search for #individual topic flows, i.e., you can select particular authors and find out who they influenced on what topic.

With this #webtool, you can analyze the #intertopic flow within computer science or #mathematics. More research areas are to come in the next weeks, e.g., #economics, #biology, #physics, etc. You can have an overview over a whole area or select interesting #topics or #years.

It is based on our recently published applied #data #science work, appeared in #scientometrics: https://doi.org/10.1007/s11192-022-04529-w

We derive a topic based #social #network from a #scientific co-authorship graph by attributing #topics to authors, based on the topics of their research work.

A new #scientometric tool based on our work on measuring #Research #Topic #Flow in co-authorship #Networks was released yesterday to the public: https://flowtest.sci-rec.org/

It is still #beta and and a bit #buggy, so please be #kind ;)