SigGPDE: scaling sparse Gaussian Processes on sequential data
Making predictions and quantifying their uncertainty when the input data is sequential is a fundamental learning challenge, recently attracting increasing attention. We develop SigGPDE, a new scalable sparse variational inference framework for Gaussian Processes (GPs) on sequential data. Our contrib...
| Glavni autori: | , , , , , |
|---|---|
| Format: | Internet publication |
| Jezik: | English |
| Izdano: |
2021
|