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ORCIDTobias Hatt
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2020 – today
- 2024
[c11]Tobias Hatt, Stefan Feuerriegel:
Sequential Deconfounding for Causal Inference with Unobserved Confounders. CLeaR 2024: 934-956- [c10]Milan Kuzmanovic
, Dennis Frauen, Tobias Hatt, Stefan Feuerriegel:
Causal Machine Learning for Cost-Effective Allocation of Development Aid. KDD 2024: 5283-5294 - [i12]Milan Kuzmanovic, Dennis Frauen, Tobias Hatt, Stefan Feuerriegel:
Causal Machine Learning for Cost-Effective Allocation of Development Aid. CoRR abs/2401.16986 (2024) - 2023
- [c9]Dennis Frauen, Tobias Hatt, Valentyn Melnychuk, Stefan Feuerriegel:
Estimating Average Causal Effects from Patient Trajectories. AAAI 2023: 7586-7594 - [c8]Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel:
Estimating Conditional Average Treatment Effects with Missing Treatment Information. AISTATS 2023: 746-766 - 2022
- [c7]Daniel Tschernutter, Tobias Hatt, Stefan Feuerriegel:
Interpretable Off-Policy Learning via Hyperbox Search. ICML 2022: 21795-21827 - [c6]Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel:
Generalizing off-policy learning under sample selection bias. UAI 2022: 769-779 - [c5]Yilmazcan Özyurt, Tobias Hatt, Ce Zhang, Stefan Feuerriegel:
A Deep Markov Model for Clickstream Analytics in Online Shopping. WWW 2022: 3071-3081 - [i11]Tobias Hatt, Jeroen Berrevoets, Alicia Curth, Stefan Feuerriegel, Mihaela van der Schaar:
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects. CoRR abs/2202.12891 (2022) - [i10]Dennis Frauen, Tobias Hatt, Valentyn Melnychuk, Stefan Feuerriegel:
Estimating average causal effects from patient trajectories. CoRR abs/2203.01228 (2022) - [i9]Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel:
Estimating Conditional Average Treatment Effects with Missing Treatment Information. CoRR abs/2203.01422 (2022) - [i8]Daniel Tschernutter, Tobias Hatt, Stefan Feuerriegel:
Interpretable Off-Policy Learning via Hyperbox Search. CoRR abs/2203.02473 (2022) - [i7]Yanke Li, Tobias Hatt, Ioana Bica, Mihaela van der Schaar:
DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction. CoRR abs/2208.01373 (2022) - [i6]Tobias Hatt, Stefan Feuerriegel:
Detecting User Exits from Online Behavior: A Duration-Dependent Latent State Model. CoRR abs/2208.03937 (2022) - 2021
- [c4]Tobias Hatt, Stefan Feuerriegel:
Estimating Average Treatment Effects via Orthogonal Regularization. CIKM 2021: 680-689 - [c3]Yilmazcan Özyurt, Mathias Kraus, Tobias Hatt, Stefan Feuerriegel:
AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units. KDD 2021: 3452-3462 - [c2]Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel:
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies. ML4H@NeurIPS 2021: 143-155 - [i5]Tobias Hatt, Stefan Feuerriegel:
Estimating Average Treatment Effects via Orthogonal Regularization. CoRR abs/2101.08490 (2021) - [i4]Yilmazcan Özyurt, Mathias Kraus, Tobias Hatt, Stefan Feuerriegel:
AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units. CoRR abs/2102.04702 (2021) - [i3]Tobias Hatt, Stefan Feuerriegel:
Sequential Deconfounding for Causal Inference with Unobserved Confounders. CoRR abs/2104.09323 (2021) - [i2]Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel:
Generalizing Off-Policy Learning under Sample Selection Bias. CoRR abs/2112.01387 (2021) - [i1]Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel:
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies. CoRR abs/2112.03013 (2021) - 2020
- [c1]Tobias Hatt, Stefan Feuerriegel:
Early Detection of User Exits from Clickstream Data: A Markov Modulated Marked Point Process Model. WWW 2020: 1671-1681
Coauthor Index
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