Research map / Time series / Causal and generative time series
Learning Registered Point Processes from Idiosyncratic Observations
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use alternating registration instead of WLR | Point-process registration · MIMIC-III | risk_under: 0.018 -> 0.011 | Helped |
| Use alternating registration instead of WLR | Point-process registration · MIMIC-III | risk_over: 0.055 -> 0.009 | Helped |
| Use alternating registration instead of WLR | Point-process registration · MIMIC-III | Rank Corr.: 0.025 -> 0.053 | Helped |
| Use alternating registration instead of WLR | Point-process registration · LinkedIn | risk_under: 0.029 -> 0.025 | Helped |
| Use alternating registration instead of WLR | Point-process registration · LinkedIn | risk_over: 0.657 -> 0.010 | Helped |
| Use alternating registration instead of WLR | Point-process registration · LinkedIn | Rank Corr.: 0.344 -> 0.375 | Helped |
| Add one stitching operation (ablation) | RPP · MIMIC-III | risk_under: 0.011 -> 0.003 | Helped |
| Add one stitching operation (ablation) | RPP · MIMIC-III | risk_over: 0.009 -> 0.002 | Helped |
| Add one stitching operation (ablation) | RPP · MIMIC-III | Rank Corr.: 0.053 -> 0.053 | No clear effect |
| Add one stitching operation (ablation) | RPP · LinkedIn | risk_under: 0.025 -> 0.005 | Helped |
| Add one stitching operation (ablation) | RPP · LinkedIn | risk_over: 0.010 -> 0.006 | Helped |
| Add one stitching operation (ablation) | RPP · LinkedIn | Rank Corr.: 0.375 -> 0.387 | Helped |
Closest papers by meaning
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- Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes (NeurIPS 2019 · similarity 0.87)
- UNIPoint: Universally Approximating Point Processes Intensities (AAAI 2021 · similarity 0.87)
- Decomposable Transformer Point Processes (NeurIPS 2024 · similarity 0.85)
- EasyTPP: Towards Open Benchmarking Temporal Point Processes (ICLR 2024 · similarity 0.85)
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