Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data
Authors: Junjie Liang, Weijieying Ren, Hanifi Sahar, Vasant Honavar
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We describe the results of extensive experiments demonstrating that ICDKGP substantially outperforms the state-of-the-art longitudinal methods on data with both smoothly and non-smoothly varying outcomes. |
| Researcher Affiliation | Academia | Junjie Liang, Weijieying Ren, Hanifi Sahar, Vasant Honavar The Pennsylvania State University jliang282@outlook.com, {wjr5337, szh6071, vuh14}@psu.edu |
| Pseudocode | No | The paper describes its model and mathematical formulations but does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | Full implementation details and the Appendix can be accessed through https://github.com/junjieliang672/ICDKGP/blob/main/ICDKGP-AAAI24 appendix.pdf. This link points to a PDF appendix, not directly to the source code repository. |
| Open Datasets | Yes | We used three real-world longitudinal data sets, each with some degree of discontinuities. (i) The SWAN (Sutton-Tyrrell et al. 2005) data is taken from a longitudinal study of women s health in midlife. (ii) GSS (Smith et al. 2015) data is taken from a 30-year longitudinal study... (iii) TADPOLE (Marinescu et al. 2018) data is taken from the Alzheimer s Disease Neuroimaging Initiative (ADNI) longitudinal study... |
| Dataset Splits | Yes | We evaluated the performance of each model on each regression task using 10 independent runs, using 50%, 20%, and 30% of data for training, validation, and testing respectively. |
| Hardware Specification | No | The paper does not provide any specific hardware details such as GPU/CPU models, processor types, or memory used for running the experiments. |
| Software Dependencies | No | The paper refers to implementation details in an appendix, but does not specify software dependencies with version numbers (e.g., Python version, library versions) in the main text. |
| Experiment Setup | No | The paper states that 'Full implementation details and the Appendix can be accessed through https://github.com/junjieliang672/ICDKGP/blob/main/ICDKGP-AAAI24 appendix.pdf,' implying hyperparameter and setup details are there, but they are not explicitly provided within the main body of the paper. |