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..
A Complete Variational Tracker
Authors: Ryan D Turner, Steven Bottone, Bhargav Avasarala
NeurIPS 2014 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate the applicability of our method on radar tracking and computer vision problems. We use the VS-PETS 2003 soccer player data set as a real data example to validate our method. |
| Researcher Affiliation | Industry | Ryan Turner Northrop Grumman Corp. EMAIL Steven Bottone Northrop Grumman Corp. EMAIL Bhargav Avasarala Northrop Grumman Corp. EMAIL |
| Pseudocode | No | The paper describes algorithms such as 'variational algorithm' and 'loopy belief propagation', and provides mathematical derivations of steps, but it does not include a dedicated pseudocode block or a clearly labeled algorithm section. |
| Open Source Code | No | The paper does not contain any explicit statement about making the source code available or provide a link to a code repository. |
| Open Datasets | Yes | We borrow the radar tracking example of the OMGP paper [18]." and "We use the VS-PETS 2003 soccer player data set as a real data example to validate our method. ... Soccer data source: http://www.cvg.rdg.ac.uk/slides/pets.html. |
| Dataset Splits | No | The paper states, 'The parameters for the NCV, R, PD, λ, and the track meta-state parameters were trained by optimizing the variational lower bound Lβ on the first 1000 frames...' and 'We split the remainder of the data into 70 sequences of K = 20 frames for a test set.' This indicates training and testing sets, but no explicit validation set. |
| Hardware Specification | No | The paper does not provide any specific hardware details such as GPU/CPU models, processor types, or memory amounts used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers, such as library or solver names, that are needed to replicate the experiment. |
| Experiment Setup | Yes | We borrow the radar tracking example... We have made the example more realistic by adding clutter λ = 8 and missed detections PD = 0.5". For the soccer example: "The parameters for the NCV, R, PD, λ, and the track meta-state parameters were trained by optimizing the variational lower bound Lβ on the first 1000 frames". |