Julius von Kügelgen - Google Scholar Citations

2017201820194 3 3

Marco LoogDelft University of Technology & University of CopenhagenVerified email at tudelft.nl
Alexander MeyDelft University of TechnologyVerified email at tudelft.nl
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
Adrian WellerPrincipal Research Fellow, Machine Learning, University of CambridgeVerified email at eng.cam.ac.uk
Paul K RubensteinUniversity of Cambridge / Max Planck Institute for Intelligent SystemsVerified email at cam.ac.uk

Julius von Kügelgen

MPI for Intelligent Systems, Tübingen & University of Cambridge

Verified email at tuebingen.mpg.de - Homepage


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A bacterial size law revealed by a coarse-grained model of cell physiology F Bertaux, J Von Kügelgen, S Marguerat, V Shahrezaei bioRxiv, 078998, 2020	8*	2020
Semi-supervised learning, causality and the conditional cluster assumption J von Kügelgen, M Loog, A Mey, B Schölkopf arXiv preprint arXiv:1905.12081, 2019	1	2019
Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features J Kügelgen, A Mey, M Loog The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	1	2019
Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks J von Kügelgen, PK Rubenstein, B Schölkopf, A Weller arXiv preprint arXiv:1910.03962, 2019		2019

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