Talks

Kook L (2023). “Model-based causal feature selection for general response types.” Invited talk, UZH Econometrics Seminar.

Kook L (2023). “Distributional regression with neural networks in R.” Invited talk, CMStatistics Berlin.

Kook L (2023). “Invariant causal prediction for non-additive noise models.” Contributed talk, EMS Warsaw.

Kook L (2023). “Invariant causal prediction for non-additive noise models.” Contributed talk, NORDSTAT Gothenburg.

Kook L (2022). “Ensembling deep transformation models.” Invited talk, CMStatistics London.

Kook L, Herzog L, Dürr O, Hothorn T, Wegener S, Sick B (2021). “Interpretable effect estimates in semi-structured deep distributional regression.” ISCB’42, Lyon (online).

Kook L (2021). “Ordinal neural network transformation models.” Invited talk, LMU Munich (online).

Kook L, Herzog L, Grabner H, Wegener S, Sick B (2021). “Improving treatment decisions in acute stroke using deep-learning based risk analysis.” Freenovation Science Forum (online).