Christina Heinze-Deml

Cited by

	All	Since 2017
Citations	613	591
h-index	10	10
i10-index	10	10

220

110

165

201520162017201820192020202120223 15 28 63 69 131 205 94

Public access

View all

3 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Nicolai MeinshausenProfessor of Statistics, ETH ZurichVerified email at stat.math.ethz.ch
Jonas PetersProfessor of Statistics, University of CopenhagenVerified email at math.ku.dk
Brian McWilliamsResearch Scientist, DeepMindVerified email at google.com
Marloes MaathuisETH ZurichVerified email at stat.math.ethz.ch
Gabriel KrummenacherZühlke Engineering AGVerified email at zuehlke.com
Dominik RothenhäuslerStanford UniversityVerified email at stanford.edu
Ioannis TsamardinosProfessor, Computer Science Department, University of CreteVerified email at csd.uoc.gr
Sofia TriantafillouUniversity of Crete, University of PittsburghVerified email at pitt.edu
Vincenzo LaganiAssociate Professor, Ilia State UniversityVerified email at iliauni.edu.ge
Angelika SchmidtBiomedical Center Munich, Institute for ImmunologyVerified email at bmc.med.lmu.de
Jesper TegnérProfessor. Bio, CS, BioE, STAT programs,KAUST, Strategic Professor, KarolinskaVerified email at kaust.edu.sa
Fanny YangETH ZurichVerified email at inf.ethz.ch
Sebastian SippelETH ZurichVerified email at env.ethz.ch
hastagiri vanchinathanSharechatVerified email at sharechat.co
Angeline G PendergrassCornell University and National Center for Atmospheric ResearchVerified email at ucar.edu
Juan L. GamellaETH ZürichVerified email at stat.math.ethz.ch
Flavio LehnerCornell University and National Center for Atmospheric ResearchVerified email at cornell.edu
Diane BouchacourtFacebook AI ResearchVerified email at fb.com
Michel BesserveMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de
Reto KnuttiProfessor for Climate Physics, ETH ZurichVerified email at env.ethz.ch

Christina Heinze-Deml

Apple AI/ML Research

Verified email at apple.com - Homepage

Causality Machine Learning Computational Statistics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Invariant causal prediction for nonlinear models C Heinze-Deml, J Peters, N Meinshausen Journal of Causal Inference 6 (2), 2018	143	2018
Causal structure learning C Heinze-Deml, MH Maathuis, N Meinshausen arXiv preprint arXiv:1706.09141, 2017	116	2017
Conditional variance penalties and domain shift robustness C Heinze-Deml, N Meinshausen Machine Learning 110 (2), 303-348, 2021	109*	2021
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions D Rothenhäusler, C Heinze, J Peters, N Meinshausen Advances in Neural Information Processing Systems (NIPS) 29, 2015, 2015	46	2015
Random projections for large-scale regression GA Thanei, C Heinze, N Meinshausen Big and complex data analysis, 51-68, 2017	40	2017
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections C Heinze, B McWilliams, N Meinshausen Proceedings of the 19th International Conference on Artificial Intelligence …, 2016	38	2016
Loco: Distributing ridge regression with random projections C Heinze, B McWilliams, N Meinshausen, G Krummenacher arXiv preprint arXiv:1406.3469, 2014	30*	2014
Predicting causal relationships from biological data: Applying automated causal discovery on mass cytometry data of human immune cells S Triantafillou, V Lagani, C Heinze-Deml, A Schmidt, J Tegner, ... Scientific reports 7 (1), 1-11, 2017	28	2017
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness F Yang, Z Wang, C Heinze-Deml Advances in Neural Information Processing Systems (NeurIPS) 33, 2019, 2019	24	2019
Active invariant causal prediction: Experiment selection through stability JL Gamella, C Heinze-Deml Advances in Neural Information Processing Systems (NeurIPS) 34, 2020, 2020	11	2020
Preserving privacy between features in distributed estimation C Heinze‐Deml, B McWilliams, N Meinshausen stat 7 (1), e189, 2018	9	2018
CompareCausalNetworks: interface to diverse estimation methods of causal networks C Heinze-Deml, N Meinshausen R package, 2017	7*	2017
Think before you act: A simple baseline for compositional generalization C Heinze-Deml, D Bouchacourt arXiv preprint arXiv:2009.13962, 2020	6	2020
Latent Linear Adjustment Autoencoder v1. 0: a novel method for estimating and emulating dynamic precipitation at high resolution C Heinze-Deml, S Sippel, AG Pendergrass, F Lehner, N Meinshausen Geoscientific Model Development 14 (8), 4977-4999, 2021	3	2021
Perturbations and Causality in Gaussian Latent Variable Models A Taeb, JL Gamella, C Heinze-Deml, P Bühlmann arXiv preprint arXiv:2101.06950v3, 2021	3	2021
Transfer learning for estimating dynamic precipitation across different climate models J Kuettel, S Sippel, C Heinze-Deml, R Knutti, N Meinshausen EGU22, 2022		2022
Package ‘CondIndTests’ C Heinze-Deml, J Peters, AMS Munk, MC Heinze-Deml, T LazyData		2019
Computational Causality and Learning from Partitioned Data C Heinze-Deml ETH Zurich, 2018		2018
Uncovering the structure of complex data: progresses in machine learning and causal inference M Besserve, C Heinze-Deml Data Learning and Inference (DALI 2017), 2017		2017
Package ‘backShift’ C Heinze https://cran.r-project.org/web/packages/backShift/backShift.pdf, 2015		2015

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow this author

Cited by

Co-authors