Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes
Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Bayesian model averaging across kernels instead of only the highest-posterior kernel (ablation) | VBKS · Swissgrid | RMSE (MWh): 160.6 -> 155.9; 162.1 -> 159.3; 162.0 -> 159.9; 159.4 -> 156.2; 159.0 -> 156.2; 159.2 -> 156.7; 159.2 -> 156.9; 163.3 -> | Helped |
| Use Bayesian model averaging across kernels instead of only the highest-posterior kernel (ablation) | VBKS · IEQ | RMSE (°C): $0.416$ -> 0.380; 0.380 -> 0.371; 0.383 -> 0.373; 0.386 -> 0.374; 0.379 -> 0.367; 0.386 -> 0.372; 0.380 -> 0.370; 0.384 | Helped |
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