Research map / Probabilistic and scientific modeling / Variational and generative sampling
Slice Sampling on Hamiltonian Trajectories
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use HSS (slice sampling along Hamiltonian trajectories via uniform transform) instead of ESS on GP regression | latent GP regression · GP regression, D=1 to 10 | effective samples | Hurt |
| Use HSS instead of HMC for updating cluster parameters in the PY mixture model | Pitman-Yor mixture model · galaxy dataset | effective samples (JLL) per run time | Helped |
| Degrade HSS posterior-prior match by larger sample size (more data) | HSS on PY model · galaxy dataset | sampler performance | Hurt |
| Use tuned small HMC steps vs. larger steps (larger step sizes) | HMC in PY model · galaxy dataset | effective sample size | Helped |
Closest papers by meaning
- Towards Unifying Hamiltonian Monte Carlo and Slice Sampling (NeurIPS 2016 · similarity 0.92)
- Gibbsian Polar Slice Sampling (ICML 2023 · similarity 0.90)
- Slice Sampling Reparameterization Gradients (NeurIPS 2021 · similarity 0.89)
- Parallel Affine Transformation Tuning of Markov Chain Monte Carlo (ICML 2024 · similarity 0.86)
- Metropolis Adjusted Microcanonical Hamiltonian Monte Carlo (NeurIPS 2025 · similarity 0.85)
- Chain of Log-Concave Markov Chains (ICLR 2024 · similarity 0.85)
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