Englisch

Linzner, D. ; Koeppl, H. (2021)
Active Learning of Continuous-time Bayesian Networks through Interventions.
38th International Conference on Machine Learning. virtual Conference (18.07.2021-24.07.2021)
Konferenzveröffentlichung, Bibliographie

Engelmann, N. ; Linzner, D. ; Koeppl, H. (2020)
Continuous-Time Bayesian Networks with Clocks.
International Conference on Machine Learning 2020. virtual Conference (12.07.2019-18.07.2019)
Konferenzveröffentlichung, Bibliographie

Linzner, D. ; Heinz, K. (2020)
A Variational Perturbative Approach to Planning in Graph-based Markov Decision Processes.
AAAI-20 - Thirty-Fourth AAAI Conference on Artificial Intelligence. New York, USA (07.02.2020-12.02.2020)
Konferenzveröffentlichung, Bibliographie

Linzner, D. ; Schmidt, M. ; Koeppl, H. (2019)
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
33rd Conference on Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada (09.12.2019-13.12.2019)
Konferenzveröffentlichung, Bibliographie

Linzner, D. ; Koeppl, H. (2018)
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
32. Conference on Neural Information Processing Systems. Montreal, Canada (03.12.2018-08.12.2018)
Konferenzveröffentlichung, Bibliographie