Revealing Common Statistical Behaviors in Heterogeneous Populations
Authors: Andrey Zhitnikov, Rotem Mulayoff, Tomer Michaeli
ICML 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We illustrate the effectiveness of our methods through extensive simulations as well as on real-data from f MRI scans and from arterial blood pressure and photoplethysmogram measurements. |
| Researcher Affiliation | Academia | Electrical Engineering Dept., Technion, Israel. |
| Pseudocode | Yes | Algorithm 1 Common covariance estimation. ... Algorithm 2 Common density estimation. |
| Open Source Code | No | The paper does not provide any explicit statements or links indicating that the source code for the methodology is open-sourced or publicly available. |
| Open Datasets | Yes | ADHD200-preprocessed dataset (Bellec et al., 2017). ... MIMIC 2 dataset (Kachuee et al., 2015). |
| Dataset Splits | No | The paper uses datasets but does not explicitly provide details on train/validation/test splits, specific percentages, or sample counts for reproducing data partitioning. |
| Hardware Specification | Yes | The running time of Alg. 1 was about 10s on an 8 core Intel i7-6700 with 16GB of RAM working at 3.40GHz. |
| Software Dependencies | No | We used the nilearn and scikit-learn python packages (Abraham et al., 2014; Pedregosa et al., 2011; Buitinck et al., 2013). |
| Experiment Setup | Yes | In particular, we used preprocessed resting state f MRI data... We removed nuisance variance... applied a temporal bandpass filter (0.009 Hz < f < 0.08 Hz) ... and a spatial Gaussian filter (6mm FWHM). ... For each subject, we then estimated the 2D pdf of ABP and PPG using Gaussian KDE with bandwidth 0.08. |