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..
Cooperative Distribution Alignment via JSD Upper Bound
Authors: Wonwoong Cho, ZIYU GONG, David I. Inouye
NeurIPS 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We show empirical results on both simulated and real-world datasets to demonstrate the benefits of our approach. |
| Researcher Affiliation | Academia | Wonwoong Cho Purdue University EMAIL Purdue University EMAIL David I. Inouye Purdue University EMAIL Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN |
| Pseudocode | Yes | Algorithm 1 Training algorithm for AUB |
| Open Source Code | Yes | Code is available at https://github.com/inouye-lab/alignment-upper-bound. |
| Open Datasets | Yes | In both experiments, we used four UCI tabular datasets [29] (MINIBOONE, GAS, HEPMASS, and POWER), following the same preprocessing as the MAF paper [30]. ... We perform an image translation task on MNIST dataset4 [31] ... Domain Adaptation on USPS-MNIST dataset |
| Dataset Splits | Yes | Train, validation, and test sets are 80%, 10%, and 10% of the data respectively. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running experiments. |
| Software Dependencies | No | The paper mentions software components like 'Real NVP' but does not provide specific version numbers for any software dependencies. |
| Experiment Setup | No | The paper mentions 'Implementation details are provided in ??' which suggests they are outside the main text. Algorithm 1 lists some general parameters like 'batch size; learning rate η; maximum epoch Emax' but no specific values are given in the main body of the paper. |