2022

Sequential Causal Effect Variational Autoencoder: Time Series Causal Link Estimation under Hidden Confounding
Violeta Teodora Trifunov and Maha Shadaydeh and Joachim Denzler.
arXiv preprint arXiv:2209.11497. 2022.
[bibtex] [web] [abstract]
Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions
Violeta Teodora Trifunov and Maha Shadaydeh and Joachim Denzler.
NeurIPS Workshop on A Causal View on Dynamical Systems (NeurIPS-WS). 2022.
[bibtex] [pdf] [web] [abstract]

2021

Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning
Violeta Teodora Trifunov and Maha Shadaydeh and Björn Barz and Joachim Denzler.
IEEE International Conference on Machine Learning and Applications (ICMLA). Pages 166-172. 2021.
[bibtex] [pdf] [web] [abstract]
A Data-Driven Approach to Partitioning Net Ecosystem Exchange Using a Deep State Space Model
Violeta Teodora Trifunov and Maha Shadaydeh and Jakob Runge and Markus Reichstein and Joachim Denzler.
IEEE Access. 9: pages 107873-107883. 2021.
[bibtex] [web] [abstract]

2019

Causal Link Estimation under Hidden Confounding in Ecological Time Series
Violeta Teodora Trifunov and Maha Shadaydeh and Jakob Runge and Veronika Eyring and Markus Reichstein and Joachim Denzler.
International Workshop on Climate Informatics (CI). 2019.
[bibtex] [pdf] [abstract]
Nonlinear Causal Link Estimation under Hidden Confounding with an Application to Time-Series Anomaly Detection
Violeta Teodora Trifunov and Maha Shadaydeh and Jakob Runge and Veronika Eyring and Markus Reichstein and Joachim Denzler.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 261-273. 2019.
[bibtex] [pdf] [abstract]

2018

Domain knowledge integration for causality analysis of carbon-cycle variables
Violeta Teodora Trifunov and Maha Shadaydeh and Jakob Runge and Veronika Eyring and Markus Reichstein and Joachim Denzler.
American Geophysical Union Fall Meeting (AGU): Abstract + Poster Presentation. 2018.
[bibtex] [web] [abstract]