Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes
Variational Inference for Gaussian Process Models with Linear Complexity
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Decouple mean and covariance bases, using a larger mean basis | Sparse variational GP regression · KUKA₁ | nMSE: 0.128 -> 0.037 | Helped |
| Decouple mean and covariance bases, using a larger mean basis | Sparse variational GP regression · KUKA₁ | VLB (10^5): 0.649 -> 1.262 | Helped |
| Decouple mean and covariance bases, using a larger mean basis | Sparse variational GP regression · MuJoCo₁ | nMSE: 0.099 -> 0.072 | Helped |
| Decouple mean and covariance bases, using a larger mean basis | Sparse variational GP regression · MuJoCo₁ | VLB (10^5): 4.543 -> 6.007 | Helped |
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- Sparse Variational Student-t Processes (AAAI 2024 · similarity 0.90)
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