Linzner, Dominik

6 publications

MLOSS 2025 BoFire: Bayesian Optimization Framework Intended for Real Experiments Johannes P. Dürholt, Thomas S. Asche, Johanna Kleinekorte, Gabriel Mancino-Ball, Benjamin Schiller, Simon Sung, Julian Keupp, Aaron Osburg, Toby Boyne, Ruth Misener, Rosona Eldred, Chrysoula Kappatou, Robert M. Lee, Dominik Linzner, Wagner Steuer Costa, David Walz, Niklas Wulkow, Behrang Shafei

ICML 2021 Active Learning of Continuous-Time Bayesian Networks Through Interventions Dominik Linzner, Heinz Koeppl

AAAI 2020 A Variational Perturbative Approach to Planning in Graph-Based Markov Decision Processes Dominik Linzner, Heinz Koeppl

ICML 2020 Continuous Time Bayesian Networks with Clocks Nicolai Engelmann, Dominik Linzner, Heinz Koeppl

NeurIPS 2019 Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data Dominik Linzner, Michael Schmidt, Heinz Koeppl

NeurIPS 2018 Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data Dominik Linzner, Heinz Koeppl