Dominik Linzner

13 papers A* 5Journal 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
BoFire: Bayesian Optimization Framework Intended for Real Experiments.
J. Mach. Learn. Res.
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
2024 J jnl
BoFire: Bayesian Optimization Framework Intended for Real Experiments.
CoRR
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, Wagner Steuer Costa, Chrysoula Kappatou, Robert M. Lee, Dominik Linzner, David Walz, Niklas Wulkow, Behrang Shafei
2021 A* conf
Active Learning of Continuous-time Bayesian Networks through Interventions.
ICML
Dominik Linzner, Heinz Koeppl
2021 J jnl
Active Learning of Continuous-time Bayesian Networks through Interventions.
CoRR
Dominik Linzner, Heinz Koeppl
2021 — —
Scalable Inference in Graph-coupled Continuous-time Markov Chains.
Dominik Linzner
2020 A* conf
A Variational Perturbative Approach to Planning in Graph-Based Markov Decision Processes.
AAAI
Dominik Linzner, Heinz Koeppl
2020 A* conf
Continuous Time Bayesian Networks with Clocks.
ICML
Nicolai Engelmann, Dominik Linzner, Heinz Koeppl
2020 J jnl
Continuous-Time Bayesian Networks with Clocks.
CoRR
Nicolai Engelmann, Dominik Linzner, Heinz Koeppl
2019 J jnl
A Variational Perturbative Approach to Planning in Graph-based Markov Decision Processes.
CoRR
Dominik Linzner, Heinz Koeppl
2019 A* conf
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
NeurIPS
Dominik Linzner, Michael Schmidt, Heinz Koeppl
2019 J jnl
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
CoRR
Dominik Linzner, Michael Schmidt, Heinz Koeppl
2018 A* conf
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
NeurIPS
Dominik Linzner, Heinz Koeppl
2018 J jnl
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
CoRR
Dominik Linzner, Heinz Koeppl