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Nicolai Meinshausen
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2020 – today
- 2024
- [j11]Drago Plecko, Nicolas Bennett, Nicolai Meinshausen:
fairadapt: Causal Reasoning for Fair Data Preprocessing. J. Stat. Softw. 110(4) (2024) - [i13]Xinwei Shen, Nicolai Meinshausen:
Distributional Principal Autoencoders. CoRR abs/2404.13649 (2024) - 2023
- [j10]Jeffrey Näf
, Corinne Emmenegger, Peter Bühlmann, Nicolai Meinshausen:
Confidence and Uncertainty Assessment for Distributional Random Forests. J. Mach. Learn. Res. 24: 366:1-366:77 (2023) - [i12]Xinwei Shen
Engression: Extrapolation for Nonlinear Regression? CoRR abs/2307.00835 (2023) - 2022
- [j9]Domagoj Cevid, Loris Michel, Jeffrey Näf
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression. J. Mach. Learn. Res. 23: 333:1-333:79 (2022) - [c6]Andrew Jesson, Alyson Douglas, Peter Manshausen, Maëlys Solal, Nicolai Meinshausen, Philip Stier, Yarin Gal, Uri Shalit:
Scalable Sensitivity and Uncertainty Analyses for Causal-Effect Estimates of Continuous-Valued Interventions. NeurIPS 2022 - [i11]Andrew Jesson, Alyson Douglas, Peter Manshausen, Nicolai Meinshausen, Philip Stier, Yarin Gal, Uri Shalit:
Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions. CoRR abs/2204.10022 (2022) - [i10]Enikö Székely, Sebastian Sippel, Nicolai Meinshausen, Guillaume Obozinski, Reto Knutti:
Robust detection and attribution of climate change under interventions. CoRR abs/2212.04905 (2022) - 2021
- [j8]Christina Heinze-Deml
Conditional variance penalties and domain shift robustness. Mach. Learn. 110(2): 303-348 (2021) - [i9]Michael Moor, Nicolas Bennett, Drago Plecko, Max Horn, Bastian Rieck, Nicolai Meinshausen, Peter Bühlmann, Karsten M. Borgwardt:
Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning. CoRR abs/2107.05230 (2021) - [i8]Drago Plecko, Nicolas Bennett, Nicolai Meinshausen:
fairadapt: Causal Reasoning for Fair Data Pre-processing. CoRR abs/2110.10200 (2021) - 2020
- [c5]Adrian Egli
SPHN/PHRT: Forming a Swiss-Wide Infrastructure for Data-Driven Sepsis Research. MIE 2020: 1163-1167 - [i7]Domagoj Cevid, Loris Michel, Nicolai Meinshausen, Peter Bühlmann:
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression. CoRR abs/2005.14458 (2020)
2010 – 2019
- 2019
- [i6]Drago Plecko, Nicolai Meinshausen:
Fair Data Adaptation with Quantile Preservation. CoRR abs/1911.06685 (2019) - 2018
- [j7]Gian-Andrea Thanei, Nicolai Meinshausen, Rajen Dinesh Shah:
The xyz algorithm for fast interaction search in high-dimensional data. J. Mach. Learn. Res. 19: 37:1-37:42 (2018) - [c4]Nicolai Meinshausen:
Causality from a Distributional Robustness Point of View. DSW 2018: 6-10 - 2017
- [j6]Rajen Dinesh Shah, Nicolai Meinshausen:
On $b$-bit Min-wise Hashing for Large-scale Regression and Classification with Sparse Data. J. Mach. Learn. Res. 18: 178:1-178:42 (2017) - [i5]Christina Heinze-Deml, Brian McWilliams, Nicolai Meinshausen:
Preserving Differential Privacy Between Features in Distributed Estimation. CoRR abs/1703.00403 (2017) - [i4]Christina Heinze-Deml, Nicolai Meinshausen:
Guarding Against Adversarial Domain Shifts with Counterfactual Regularization. CoRR abs/1710.11469 (2017) - 2016
- [j5]Peter Bühlmann
Magging: Maximin Aggregation for Inhomogeneous Large-Scale Data. Proc. IEEE 104(1): 126-135 (2016) - [c3]Christina Heinze, Brian McWilliams, Nicolai Meinshausen:
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections. AISTATS 2016: 875-883 - [c2]Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M. Buhmann, Nicolai Meinshausen:
Scalable Adaptive Stochastic Optimization Using Random Projections. NIPS 2016: 1750-1758 - [i3]Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M. Buhmann, Nicolai Meinshausen:
Scalable Adaptive Stochastic Optimization Using Random Projections. CoRR abs/1611.06652 (2016) - 2015
- [c1]Dominik Rothenhäusler, Christina Heinze, Jonas Peters, Nicolai Meinshausen:
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions. NIPS 2015: 1513-1521 - [i2]Christina Heinze, Brian McWilliams, Nicolai Meinshausen:
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections. CoRR abs/1506.02554 (2015) - 2014
- [j4]Tze Choy, Nicolai Meinshausen:
Sparse distance metric learning. Comput. Stat. 29(3): 515-528 (2014) - [j3]Rajen Dinesh Shah, Nicolai Meinshausen:
Random intersection trees. J. Mach. Learn. Res. 15(1): 629-654 (2014) - 2012
- [i1]Steffen L. Lauritzen, Nicolai Meinshausen:
Discussion: Latent variable graphical model selection via convex optimization. CoRR abs/1211.0806 (2012)
2000 – 2009
- 2007
- [j2]Nicolai Meinshausen:
Relaxed Lasso. Comput. Stat. Data Anal. 52(1): 374-393 (2007) - 2006
- [j1]Nicolai Meinshausen:
Quantile Regression Forests. J. Mach. Learn. Res. 7: 983-999 (2006)
Coauthor Index
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