Automated Author ProfileYang, Min
同济大学
Yang, Min
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author'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: 2.0 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset is the supporting data of the paper "Probabilistic Automata-based Method for Enhancing Performance of Deep Reinforcement Learning Systems". The model JSSP-model.zip can be downloaded from https://github.com/zcajiayin/L2D, the model pong-v4.zip can be downloaded from https://github.com/greydanus/baby-a3c, and the model ppo2_cartpole.zip can be downloaded from https://github.com/DLR-RM/rl-trained-agents/tree/master/ppo. The core codes of the framework proposed in the paper are: cluster.py and BFS.py.
Authors
- Yang, Min