Persistence Bag-of-Words for Topological Data Analysis
Authors: Bartosz Zieliński, Michał Lipiński, Mateusz Juda, Matthias Zeppelzauer, Paweł Dłotko
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Comprehensive experiments show that the new representation achieves state-of-the-art performance and beyond in much less time than alternative approaches.Sections 5 and 6 present experimental setup, results and discussion. |
| Researcher Affiliation | Academia | 1The Institute of Computer Science and Computer Mathematics, Faculty of Mathematics and Computer Science, Jagiellonian University 2Media Computing Group, Institute of Creative Media Technologies, St. P olten University of Applied Sciences, 3Department of Mathematics and Swansea Academy of Advanced Computing, Swansea University |
| Pseudocode | No | The paper does not contain any clearly labeled pseudocode or algorithm blocks. Method steps are described in prose and mathematical formulas. |
| Open Source Code | Yes | The code of our experiments is implemented in Matlab9. [Footnote 9: https://github.com/bziiuj/pcodebooks] |
| Open Datasets | Yes | we evaluate all approaches on a set of synthetically generated shape classes from [Adams et al., 2017]. ...real-world datasets for geometry-informed material recognition (Geo Mat) [De Gol et al., 2016], classification of social network graphs (reddit-5k, reddit-12k) [Hofer et al., 2017], analysis of 3D surface texture (Petro Surf3D) [Zeppelzauer et al., 2017], and 3D shape segmentation [Carri ere et al., 2017]. |
| Dataset Splits | Yes | To enhance the comparability we employ (if available) the original train/test division of the datasets. To find optimal parameters for each evaluated approach, we run a grid search including cross-validation over the hyperparameters of all approaches (see Table 1 in SMa). |
| Hardware Specification | No | The paper does not explicitly describe the specific hardware (e.g., CPU/GPU models, memory) used for running the experiments. |
| Software Dependencies | No | The code of our experiments is implemented in Matlab9. For bag-of-words we employ the VLFeat library [Vedaldi and Fulkerson, 2008]. No version numbers are provided for these software dependencies. |
| Experiment Setup | Yes | To find optimal parameters for each evaluated approach, we run a grid search including cross-validation over the hyperparameters of all approaches (see Table 1 in SMa). |