Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes
Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regression
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add probabilistic ordinal embeddings to classification regression | Classification regression · MORPH II | MAE: 2.64 -> 2.35 | Helped |
| Add probabilistic ordinal embeddings to ranking regression | Ranking regression · MORPH II | MAE: 2.62 -> 2.43 | Helped |
| Add probabilistic embeddings to classification regression (ablation) | Classification regression · MORPH II | MAE: 2.64 -> 2.45 | Helped |
| Add ordinal distribution constraint to classification probabilistic embeddings (ablation) | Classification regression · MORPH II | MAE: 2.45 -> 2.37 | Helped |
| Add VIB regularization to classification probabilistic embeddings (ablation) | Classification regression · MORPH II | MAE: 2.45 -> 2.39 | Helped |
| Add VIB regularization to classification with ordinal constraint (ablation) | Classification regression · MORPH II | MAE: 2.37 -> 2.35 | Helped |
| Add probabilistic embeddings to ranking regression (ablation) | Ranking regression · MORPH II | MAE: 2.62 -> 2.53 | Helped |
| Add ordinal distribution constraint to ranking probabilistic embeddings (ablation) | Ranking regression · MORPH II | MAE: 2.53 -> 2.45 | Helped |
| Add VIB regularization to ranking probabilistic embeddings (ablation) | Ranking regression · MORPH II | MAE: 2.53 -> 2.48 | Helped |
| Use symmetric KL with margin 2 rather than the selected margin 5 (ablation) | POE · MORPH II | MAE: 2.35 -> 2.35 | No clear effect |
| Increase ordinal-loss weight alpha to 1e-2 (ablation) | POE · MORPH II | MAE: 2.35 -> 3.89 | Hurt |
| Increase VIB-loss weight beta to 1e-2 (ablation) | POE · MORPH II | MAE: 2.35 -> 8.36 | Hurt |
Closest papers by meaning
- Finite Sample Prediction and Recovery Bounds for Ordinal Embedding (NeurIPS 2016 · similarity 0.89)
- Robust Ordinal Embedding from Contaminated Relative Comparisons (AAAI 2019 · similarity 0.88)
- Stochastic Non-Convex Ordinal Embedding With Stabilized Barzilai-Borwein Step Size (AAAI 2018 · similarity 0.86)
- SLACE: A Monotone and Balance-Sensitive Loss Function for Ordinal Regression (AAAI 2025 · similarity 0.86)
- Second-Order Uncertainty Quantification: A Distance-Based Approach (ICML 2024 · similarity 0.84)
- Learning from Uncertain Data: From Possible Worlds to Possible Models (NeurIPS 2024 · similarity 0.84)
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