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ORCIDDominik Linzner
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2020 – today
- 2024
[i6]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:
BoFire: Bayesian Optimization Framework Intended for Real Experiments. CoRR abs/2408.05040 (2024)- 2021
- [b1]Dominik Linzner:
Scalable Inference in Graph-coupled Continuous-time Markov Chains. Technical University of Darmstadt, Germany, 2021 - [c5]Dominik Linzner, Heinz Koeppl:
Active Learning of Continuous-time Bayesian Networks through Interventions. ICML 2021: 6692-6701 - [i5]Dominik Linzner, Heinz Koeppl:
Active Learning of Continuous-time Bayesian Networks through Interventions. CoRR abs/2105.14742 (2021) - 2020
- [c4]Dominik Linzner
, Heinz Koeppl:
A Variational Perturbative Approach to Planning in Graph-Based Markov Decision Processes. AAAI 2020: 7203-7210 - [c3]Nicolai Engelmann, Dominik Linzner, Heinz Koeppl:
Continuous Time Bayesian Networks with Clocks. ICML 2020: 2912-2921 - [i4]Nicolai Engelmann, Dominik Linzner, Heinz Koeppl:
Continuous-Time Bayesian Networks with Clocks. CoRR abs/2007.00347 (2020)
2010 – 2019
- 2019
- [c2]Dominik Linzner, Michael Schmidt, Heinz Koeppl:
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data. NeurIPS 2019: 3741-3751 - [i3]Dominik Linzner, Michael Schmidt, Heinz Koeppl:
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data. CoRR abs/1909.04570 (2019) - [i2]Dominik Linzner, Heinz Koeppl:
A Variational Perturbative Approach to Planning in Graph-based Markov Decision Processes. CoRR abs/1912.01849 (2019) - 2018
- [c1]Dominik Linzner, Heinz Koeppl:
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data. NeurIPS 2018: 7891-7901 - [i1]Dominik Linzner, Heinz Koeppl:
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data. CoRR abs/1809.04294 (2018)
Coauthor Index
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