Name
Abstract | ||
|---|---|---|
The ability to deal with uncertainty in machine learning models has become equally, if not more, crucial to their predictive ability itself. For instance, during the pandemic, governmental policies and personal decisions are constantly made around uncertainties. Targeting this, Neural Process Families (NPFs) have recently shone a light on prediction with uncertainties by bridging Gaussian processe... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICDM51629.2021.00081 | 2021 IEEE International Conference on Data Mining (ICDM) |
Keywords | DocType | ISSN |
COVID-19,Uncertainty,Image color analysis,Pandemics,Neural networks,Machine learning,Gaussian processes | Conference | 1550-4786 |
ISBN | Citations | PageRank |
978-1-6654-2398-4 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuesong Wang | 1 | 0 | 0.34 |
| Lina Yao | 2 | 46 | 11.72 |
| Xianzhi Wang | 3 | 276 | 40.32 |
| Hye-Young Paik | 4 | 505 | 49.81 |
| Sen Wang | 5 | 477 | 37.24 |