9 citations · 33 across the 9 of their papers we have counts for
4 papers · 1 filter
Conditional Variance Penalties and Domain Shift Robustness
Christina Heinze-Deml, Nicolai Meinshausen
When training a deep neural network for image classification, one can broadly distinguish between two types of latent features of images that will drive the classification. We can…
Causal Structure Learning
Christina Heinze-Deml, Marloes H. Maathuis, Nicolai Meinshausen
Graphical models can represent a multivariate distribution in a convenient and accessible form as a graph. Causal models can be viewed as a special class of graphical models that n…
Invariant Causal Prediction for Nonlinear Models
Christina Heinze-Deml, Jonas Peters, Nicolai Meinshausen
An important problem in many domains is to predict how a system will respond to interventions. This task is inherently linked to estimating the system's underlying causal structure…
Preserving Differential Privacy Between Features in Distributed Estimation
Christina Heinze-Deml, Brian McWilliams, Nicolai Meinshausen
Privacy is crucial in many applications of machine learning. Legal, ethical and societal issues restrict the sharing of sensitive data making it difficult to learn from datasets th…