Statistical Topological Data Analysis - A Kernel Perspective
Authors: Roland Kwitt, Stefan Huber, Marc Niethammer, Weili Lin, Ulrich Bauer
NeurIPS 2015 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments demonstrate, on a couple of synthetic and real-world data samples, how this universal kernel enables a principled solution to the selected problem of (kernel-based) two-sample hypothesis testing. |
| Researcher Affiliation | Academia | Roland Kwitt Department of Computer Science University of Salzburg EMAIL Stefan Huber IST Austria EMAIL Marc Niethammer Department of Computer Science and BRIC UNC Chapel Hill EMAIL Weili Lin Department of Radiology and BRIC UNC Chapel Hill EMAIL Ulrich Bauer Department of Mathematics Technische Universität München (TUM) EMAIL |
| Pseudocode | No | The paper does not contain any pseudocode or algorithm blocks. |
| Open Source Code | Yes | Source code to reproduce the experiments is available at https://goo.gl/Kou BPT. |
| Open Datasets | Yes | The corpus callosum surfaces were obtained from the longitudinal dataset of the OASIS brain database3. 3available online: http://www.oasis-brains.org |
| Dataset Splits | No | The paper describes sampling methods and bootstrapping for hypothesis testing, but it does not specify explicit training/validation/test dataset splits (e.g., percentages, counts, or predefined partition files) for model training or evaluation. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for running experiments, such as CPU or GPU models, or memory specifications. |
| Software Dependencies | No | The paper mentions 'Dipha' and provides a URL but does not specify its version number or versions for any other software dependencies. |
| Experiment Setup | Yes | In all experiments, we use the proposed kernel u-PSS kernel k U σ of Eq. (5) and vary the HKS time ti in 1 = t1 < t2 < < t20 = 10.5; Regarding the u-PSS kernel scale σi, we sweep from 10^-9 = σ1 < < σ10 = 10^1. ... The test statistic under H0 is bootstrapped using B = 5 x 10^4 random permutations. |