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..
Approximate inference of marginals using the IBIA framework
Authors: Shivani Bathla, Vinita Vasudevan
NeurIPS 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Results for several benchmark sets from recent UAI competitions show that our method gives either better or comparable accuracy than existing variational and sampling based methods, with smaller runtimes. |
| Researcher Affiliation | Academia | Shivani Bathla Department of Electrical Engineering Indian Institute of Technology Madras India, 600036 EMAIL Vinita Vasudevan Department of Electrical Engineering Indian Institute of Technology Madras India, 600036 EMAIL |
| Pseudocode | No | The paper describes the algorithm steps in paragraph form and through diagrams, but it does not present a formal pseudocode or algorithm block. |
| Open Source Code | No | The paper states that IBIA has been implemented in Python3 but does not provide any information about its public availability or a link to its source code. |
| Open Datasets | Yes | Benchmarks: We used the benchmark sets included in UAI repository [Ihler, 2006] and the Bayesian network repository [Scutari, 2007]. |
| Dataset Splits | No | The paper references standard benchmark datasets but does not explicitly describe specific train/validation/test dataset splits, percentages, or methodologies for partitioning the data. |
| Hardware Specification | Yes | All experiments were carried out on an Intel i9-12900 Linux system running Ubuntu 22.04. |
| Software Dependencies | No | The paper mentions software like Lib DAI and Merlin and programming languages like Python3 and C++, but it does not specify version numbers for these software components or libraries. |
| Experiment Setup | Yes | For IBIA, we set the maximum clique size bound mcsp to 20 (referred to as IBIA20 ) when the time limit is 2 min and we set it to 23 (referred to as IBIA23 ) when the time limit is 20 min. mcsim is empirically chosen as 5 less than mcsp. |