2 citations · 2 across the 5 of their papers we have counts for
7 papers
Extrapolation in Statistical Learning with Extreme Value Theory
Sebastian Engelke, Nicola Gnecco, Anne Sabourin
Extreme value theory provides rigorous theory and statistical tools for extrapolation in machine learning, particularly in settings where traditional methods struggle due to data s…
Extremes of structural causal models
Sebastian Engelke, Nicola Gnecco, Frank Röttger
The behavior of extreme observations is well-understood for time series or spatial data, but little is known if the data generating process is a structural causal model (SCM). We s…
Achievable distributional robustness when the robust risk is only partially identified
Julia Kostin, Nicola Gnecco, Fanny Yang
In safety-critical applications, machine learning models should generalize well under worst-case distribution shifts, that is, have a small robust risk. Invariance-based algorithms…
Boosted Control Functions: Distribution generalization and invariance in confounded models
Nicola Gnecco, Jonas Peters, Sebastian Engelke +1
Modern machine learning methods and the availability of large-scale data have significantly advanced our ability to predict target quantities from large sets of covariates. However…
Extremal Random Forests
Nicola Gnecco, Edossa Merga Terefe, Sebastian Engelke
Classical methods for quantile regression fail in cases where the quantile of interest is extreme and only few or no training data points exceed it. Asymptotic results from extreme…
A causal framework for distribution generalization
Rune Christiansen, Niklas Pfister, Martin Emil Jakobsen +2
We consider the problem of predicting a response from a set of covariates when test and training distributions differ. Since such differences may have causal explanations,…
Causal discovery in heavy-tailed models
Nicola Gnecco, Nicolai Meinshausen, Jonas Peters +1
Causal questions are omnipresent in many scientific problems. While much progress has been made in the analysis of causal relationships between random variables, these methods are…