Home

Algorithm2Domain: meta-repository for benchmarking of domain adaptation performance

Work in progress

“I am a data scientist focused on model development. How well does my model generalize to a different data set? What if that data set is from a completely different statistical distribution? Or even from a completely different domain? Can I test my model on many different domain-specific datasets?”

“I work with domain data. How do I find the best model among so many out there to generalize well to my case? Can I test many models really fast on my data? Or on some open data which seems pretty close to the one I am still working to collect?”

Algorithm2Domain is a meta-repository to facilitate finding the answers. Our goal is to aggregate existing algorithms and benchmarking suits, and develop integrative pipelines for mix-and-match cross-domain benchmarking. The data sources suitable for the benchmarking will be aggregated as pointers. The main focus is put on open data sets, but in some cases (e.g. for some medical data sets) additional formalities may be required to access the data.

Contacts

This repository belongs is managed by the Institute for Biomedical Informatics (University Hospital of Cologne). Contact persons: Mayra Elwes (Mayra.Elwes at uk-koeln.de, technical questions), Ekaterina Kutafina (ekaterina.kutafina at uni-koeln.de, collaborations, contributions, development).