Mean Reversion and Heavy Tails: Characterizing Time-Series Data Using Ornstein-Uhlenbeck Processes and Machine Learning.

Raubitzek S, Schrittwieser S, Goldenits G, Schatten A, Mallinger K

Open source

DOI
10.3390/s26041263
Published
2026 Feb 14
Container
Sensors (Basel, Switzerland)
Publisher
Not recorded
Open access
yes

Credibility signals

uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.3390/s26041263,
  title = {Mean Reversion and Heavy Tails: Characterizing Time-Series Data Using Ornstein-Uhlenbeck Processes and Machine Learning.},
  author = {Raubitzek S and Schrittwieser S and Goldenits G and Schatten A and Mallinger K},
  year = {2026},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s26041263},
  url = {https://doi.org/10.3390/s26041263}
}

RIS

TY  - JOUR
TI  - Mean Reversion and Heavy Tails: Characterizing Time-Series Data Using Ornstein-Uhlenbeck Processes and Machine Learning.
AU  - Raubitzek S
AU  - Schrittwieser S
AU  - Goldenits G
AU  - Schatten A
AU  - Mallinger K
PY  - 2026
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s26041263
UR  - https://doi.org/10.3390/s26041263
ER  -

APA

S, R., S, S., G, G., A, S., & K, M. (2026). Mean Reversion and Heavy Tails: Characterizing Time-Series Data Using Ornstein-Uhlenbeck Processes and Machine Learning.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26041263

Source records