Tobias Hatt

According to our database, Tobias Hatt authored at least 14 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Causal Machine Learning for Cost-Effective Allocation of Development Aid.

Milan Kuzmanovic, Dennis Frauen, Tobias Hatt, Stefan Feuerriegel

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Sequential Deconfounding for Causal Inference with Unobserved Confounders.

Tobias Hatt, Stefan Feuerriegel

Proceedings of the Causal Learning and Reasoning, 2024

2023

Estimating Conditional Average Treatment Effects with Missing Treatment Information.

Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Estimating Average Causal Effects from Patient Trajectories.

Dennis Frauen, Tobias Hatt, Valentyn Melnychuk, Stefan Feuerriegel

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Detecting User Exits from Online Behavior: A Duration-Dependent Latent State Model.

Tobias Hatt, Stefan Feuerriegel

CoRR, 2022

DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction.

Yanke Li, Tobias Hatt, Ioana Bica, Mihaela van der Schaar

CoRR, 2022

Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects.

Tobias Hatt, Jeroen Berrevoets, Alicia Curth, Stefan Feuerriegel, Mihaela van der Schaar

CoRR, 2022

A Deep Markov Model for Clickstream Analytics in Online Shopping.

Yilmazcan Özyurt, Tobias Hatt, Ce Zhang, Stefan Feuerriegel

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Generalizing off-policy learning under sample selection bias.

Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Interpretable Off-Policy Learning via Hyperbox Search.

Daniel Tschernutter, Tobias Hatt, Stefan Feuerriegel

Proceedings of the International Conference on Machine Learning, 2022

2021

Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies.

Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel

Proceedings of the Machine Learning for Health, 2021

AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units.

Yilmazcan Özyurt, Mathias Kraus, Tobias Hatt, Stefan Feuerriegel

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Estimating Average Treatment Effects via Orthogonal Regularization.

Tobias Hatt, Stefan Feuerriegel

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Early Detection of User Exits from Clickstream Data: A Markov Modulated Marked Point Process Model.

Tobias Hatt, Stefan Feuerriegel

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020