Statistical Topological Data Analysis - A Kernel Perspective
Authors: Roland Kwitt, Stefan Huber, Marc Niethammer, Weili Lin, Ulrich Bauer
NeurIPS 2015 | Conference 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 rkwitt@gmx.at Stefan Huber IST Austria stefan.huber@ist.ac.at Marc Niethammer Department of Computer Science and BRIC UNC Chapel Hill mn@cs.unc.edu Weili Lin Department of Radiology and BRIC UNC Chapel Hill weili_lin@med.unc.edu Ulrich Bauer Department of Mathematics Technische Universität München (TUM) ulrich@bauer.org |
| 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. |