Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Reflection, Refraction, and Hamiltonian Monte Carlo
Authors: Hadi Mohasel Afshar, Justin Domke
NeurIPS 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments show that by reducing the number of rejected samples, this method improves on traditional HMC. |
| Researcher Affiliation | Academia | Hadi Mohasel Afshar Research School of Computer Science Australian National University Canberra, ACT 0200 EMAIL Justin Domke National ICT Australia (NICTA) & Australian National University Canberra, ACT 0200 EMAIL |
| Pseudocode | Yes | Algorithm 1: BASELINE & REFLECTIVE HMC ALGORITHMS |
| Open Source Code | No | The paper does not provide any explicit statements about the availability of open-source code or links to a code repository. |
| Open Datasets | No | The comparison takes place on a heavy tail piecewise model with (non-normalized) negative log probability... (18). This implies a synthetic model/distribution is used, not an existing publicly available dataset. |
| Dataset Splits | No | The paper does not specify exact percentages or sample counts for training, validation, or test splits. It describes running Markov chains and evaluating WMAE. |
| Hardware Specification | No | All algorithms are implemented in java and run on a single thread of a 3.40GHz CPU. This CPU description is too general and does not provide a specific model number or full hardware specification. |
| Software Dependencies | No | All algorithms are implemented in java. No specific version of Java or any other software dependencies with version numbers are mentioned. |
| Experiment Setup | Yes | The baseline HMC and RHMC number of steps L and step size ϵ are chosen to be 100 and 0.1 respectively. ... We use a diagonal matrix for A where, for each repetition, each entry on the main diagonal is either exp( 5) or exp(5) with equal probabilities. |