Markus Kaiser
Title
Cited by
Cited by
Year
Bayesian alignments of warped multi-output gaussian processes
M Kaiser, C Otte, T Runkler, CH Ek
arXiv preprint arXiv:1710.02766, 2017
162017
Data association with Gaussian processes
M Kaiser, C Otte, TA Runkler, CH Ek
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019
15*2019
Compositional uncertainty in deep Gaussian processes
I Ustyuzhaninov, I Kazlauskaite, M Kaiser, E Bodin, N Campbell, CH Ek
Conference on Uncertainty in Artificial Intelligence, 480-489, 2020
82020
Interpretable dynamics models for data-efficient reinforcement learning
M Kaiser, C Otte, T Runkler, CH Ek
arXiv preprint arXiv:1907.04902, 2019
32019
Bayesian decomposition of multi-modal dynamical systems for reinforcement learning
M Kaiser, C Otte, TA Runkler, CH Ek
Neurocomputing 416, 352-359, 2020
22020
Modulated Bayesian Optimization using Latent Gaussian Process Models
E Bodin, M Kaiser, I Kazlauskaite, NDF Campbell, CH Ek
stat 1050, 26, 2019
2019
Incorporating Uncertainty into Reinforcement Learning through Gaussian Processes
M Kaiser
2016
Oblivious Routing and Minimum Bisection
M Kaiser
2014
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Articles 1–8