Jonas Peters
Jonas Peters
Professor of Statistics, University of Copenhagen
Verified email at math.ku.dk - Homepage
Title
Cited by
Cited by
Year
Nonlinear causal discovery with additive noise models
P Hoyer, D Janzing, JM Mooij, J Peters, B Schölkopf
Advances in neural information processing systems 21, 689-696, 2008
5512008
Elements of causal inference
J Peters, D Janzing, B Schölkopf
The MIT Press, 2017
4492017
Counterfactual reasoning and learning systems: The example of computational advertising
L Bottou, J Peters, J Quiñonero-Candela, DX Charles, DM Chickering, ...
The Journal of Machine Learning Research 14 (1), 3207-3260, 2013
3942013
Kernel-based conditional independence test and application in causal discovery
K Zhang, J Peters, D Janzing, B Schölkopf
27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), AUAI …, 2012
3122012
Distinguishing cause from effect using observational data: methods and benchmarks
JM Mooij, J Peters, D Janzing, J Zscheischler, B Schölkopf
The Journal of Machine Learning Research 17 (1), 1103-1204, 2016
2622016
Causal inference using invariant prediction: identification and confidence intervals
J Peters, P Bühlmann, N Meinshausen
Journal of the Royal Statistical Society, Series B (with discussion) 78 (5 …, 2016
2552016
Causal discovery with continuous additive noise models
J Peters, JM Mooij, D Janzing, B Schölkopf
The Journal of Machine Learning Research 15, 2009-2053, 2014
2482014
On causal and anticausal learning
B Schölkopf, D Janzing, J Peters, E Sgouritsa, K Zhang, J Mooij
29th International Conference on Machine Learning (ICML 2012), 1255-1262, 2012, 2012
2272012
Identifiability of Gaussian structural equation models with equal error variances
J Peters, P Bühlmann
Biometrika 101 (1), 219-228, 2014
1432014
Causal inference on discrete data using additive noise models
J Peters, D Janzing, B Scholkopf
IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (12), 2436 …, 2011
1342011
CAM: Causal additive models, high-dimensional order search and penalized regression
P Bühlmann, J Peters, J Ernest
The Annals of Statistics 42 (6), 2526-2556, 2014
1182014
Regression by dependence minimization and its application to causal inference in additive noise models
J Mooij, D Janzing, J Peters, B Schölkopf
26th annual international conference on machine learning (ICML), 745-752, 2009
982009
Identifiability of causal graphs using functional models
J Peters, J Mooij, D Janzing, B Schölkopf
27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), AUAI …, 2012
962012
Invariant models for causal transfer learning
M Rojas-Carulla, B Schölkopf, R Turner, J Peters
The Journal of Machine Learning Research 19 (1), 1309-1342, 2018
85*2018
Inferring causation from time series in Earth system sciences
J Runge, S Bathiany, E Bollt, G Camps-Valls, D Coumou, E Deyle, ...
Nature communications 10 (1), 1-13, 2019
822019
Kernel-based tests for joint independence
N Pfister, P Bühlmann, B Schölkopf, J Peters
Journal of Royal Statistical Society, Series B 80, 5-31, 2017
782017
Causal inference on time series using restricted structural equation models
J Peters, D Janzing, B Schölkopf
Advances in Neural Information Processing Systems, 154-162, 2013
732013
Methods for causal inference from gene perturbation experiments and validation
N Meinshausen, A Hauser, JM Mooij, J Peters, P Versteeg, P Bühlmann
Proceedings of the National Academy of Sciences 113 (27), 7361-7368, 2016
632016
Invariant causal prediction for nonlinear models
C Heinze-Deml, J Peters, N Meinshausen
Journal of Causal Inference 6 (2), 2018
622018
Anchor regression: heterogeneous data meets causality
D Rothenhäusler, N Meinshausen, P Bühlmann, J Peters
arXiv preprint arXiv:1801.06229, 2018
622018
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