Metric on Nonlinear Dynamical Systems with Perron-Frobenius Operators
Authors: Isao Ishikawa, Keisuke Fujii, Masahiro Ikeda, Yuka Hashimoto, Yoshinobu Kawahara
NeurIPS 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We empirically illustrate our metric with an example of rotation dynamics in a unit disk in a complex plane, and evaluate the performance with real-world time-series data. |
| Researcher Affiliation | Collaboration | RIKEN Center for Advanced Intelligence Project School of Fundamental Science and Technology, Keio University The Institute of Scientific and Industrial Research, Osaka University {isao.ishikawa, keisuke.fujii.zh, masahiro.ikeda}@riken.jp yukahashimoto@keio.jp, ykawahara@sanken.osaka.ac.jp |
| Pseudocode | No | The paper describes methods mathematically and in prose, but does not include any explicit pseudocode or algorithm blocks. |
| Open Source Code | Yes | The Matlab code is available at https://github.com/keisuke198619/metric NLDS |
| Open Datasets | Yes | We used the UCR time series classification archive as open-source real-world data [5]. |
| Dataset Splits | Yes | For clear visualization, we randomly selected 20 sequences for each label from validation data... We used 40 sequences for each label and computed averaged 10-fold cross-validation error (over 10 random trials). |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for running the experiments. |
| Software Dependencies | No | The paper mentions 'Matlab code' but does not specify the version of Matlab or any other software dependencies with version numbers. |
| Experiment Setup | Yes | For the Gaussian kernel, the kernel width was set as the median of the distances from data. ... We used k-nearest neighbor classifier (k = 3) for simplicity. |