Variational Inference for Continuous-Time Switching Dynamical Systems
Authors: Lukas Köhs, Bastian Alt, Heinz Koeppl
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We extensively evaluate our algorithm under the model assumption and for real-world examples. (Abstract) ... 4 Experiments |
| Researcher Affiliation | Academia | Lukas Köhs Bastian Alt Heinz Koeppl Department of Electrical Engineering and Information Technology Technische Universität Darmstadt {lukas.koehs, bastian.alt, heinz.koeppl}@bcs.tu-darmstadt.de |
| Pseudocode | Yes | Algorithm 1: VI for hybrid processes |
| Open Source Code | Yes | An implementation of our proposed method is publicly available.1 ... 1https://git.rwth-aachen.de/bcs/projects/lk/vi-ct-shs.git |
| Open Datasets | No | The paper mentions using 'synthetic data' and 'viral ion channel Kcv MT325' data. For the latter, it notes 'We thank Gerhard Thiel and Kerri Kukovetz for providing the ion channel voltage data', indicating it's not a publicly available dataset with concrete access information provided. |
| Dataset Splits | No | The paper does not provide specific training, validation, or test dataset splits (e.g., percentages, sample counts, or references to predefined splits). |
| Hardware Specification | No | The paper does not describe the specific hardware (e.g., GPU/CPU models, memory, or cloud instance types) used for running the experiments. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers (e.g., 'Python 3.8', 'PyTorch 1.9'). |
| Experiment Setup | Yes | Both mode dynamics are given by time-independent linear drift functions f(y, z, t) = αz(βz y), (20) with set points βz and dynamics αz > 0, z Z = {1, 2}. (Section 4.1) ... We assume a mode-dependent dispersion, D = D(z). The observation time points are regularly spaced and we fix the observation covariance Σobs. (Section 4.2) ... The observation noise is a known property of the used setup; we hence fix Σobs. (Section 4.3) |