Name
Abstract | ||
|---|---|---|
Rank position forecasting in car racing is a challenging problem when using a Deep Learning-based model over time-series data. It is featured with highly complex global dependency among the racing cars, with uncertainty resulted from existing and external factors; and it is also a problem with data scarcity. Existing methods, including statistical models, machine learning regression models, and se... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IPDPS49936.2021.00082 | 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS) |
Keywords | DocType | ISSN |
Deep learning,Uncertainty,Neural networks,Predictive models,Probabilistic logic,Data models,Automobiles | Conference | 1530-2075 |
ISBN | Citations | PageRank |
978-1-6654-4066-0 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bo Peng | 1 | 9 | 2.91 |
| Jiayu Li | 2 | 0 | 2.03 |
| Selahattin Akkas | 3 | 0 | 0.34 |
| Fugang Wang | 4 | 0 | 1.01 |
| Takuya Araki | 5 | 2 | 3.13 |
| Ohno Yoshiyuki | 6 | 0 | 0.34 |
| Judy Qiu | 7 | 743 | 43.25 |