Automated Organization ProfileGoogle DeepMind; Machine Learning Group, Technische Universität Berlin; BIFOLD, Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
Google DeepMind; Machine Learning Group, Technische Universität Berlin; BIFOLD, Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.1 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
To validate that AligNet can indeed help to increase the alignment between models and humans, we used crowd-sourcing to collect a novel evaluation dataset of human semantic judgments across multiple levels of abstraction that we call Levels.
Authors
- Muttenthaler, Lukas ;
- Greff, Klaus ;
- Born, Frieda ;
- Spitzer, Bernhard ;
- Kornblith, Simon ;
- Mozer, Michael C. ;
- Müller, Klaus-Robert ;
- Unterthiner, Thomas ;
- Lampinen, Andrew K.