Research map / Probabilistic and scientific modeling / Molecules and proteins
Stochastic Nonparametric Event-Tensor Decomposition
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| model events with a Hawkes process (local triggering) on top of GP base rate, instead of a Poisson process | GP-PTF · Article, 911, UFO | test log likelihood | Helped |
| replace multilinear CP rate with nonlinear GP rate function | Poisson process tensor factorization · Article, 911, UFO | test log likelihood | Helped |
| keep exact time stamps via event-tensor instead of discretizing into time steps | CPT-PTF · Article, 911, UFO | test log likelihood | Helped |
| use Hawkes triggering with GP factors | latent factor estimation · Synthetic 10x10x10 event-tensor | cluster recovery of latent factors | Helped |
Closest papers by meaning
- Self-Modulating Nonparametric Event-Tensor Factorization (ICML 2020 · similarity 0.91)
- Nonparametric Decomposition of Sparse Tensors (ICML 2021 · similarity 0.89)
- Efficient Nonparametric Tensor Decomposition for Binary and Count Data (AAAI 2024 · similarity 0.89)
- Nonparametric Factor Trajectory Learning for Dynamic Tensor Decomposition (ICML 2022 · similarity 0.88)
- Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data (ICLR 2024 · similarity 0.87)
- Functional Complexity-adaptive Temporal Tensor Decomposition (NeurIPS 2025 · similarity 0.86)
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