Christina Heinze-Deml | DeepAI

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∙ 11/27/2022

Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions

We consider the problem of recovering the causal structure underlying ob...

0 Juan L Gamella, et al. ∙

∙ 09/29/2020

Think before you act: A simple baseline for compositional generalization

Contrarily to humans who have the ability to recombine familiar expressi...

0 Christina Heinze-Deml, et al. ∙

∙ 06/10/2020

Active Invariant Causal Prediction: Experiment Selection through Stability

A fundamental difficulty of causal learning is that causal models can ge...

0 Juan L Gamella, et al. ∙

∙ 06/26/2019

Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness

This work provides theoretical and empirical evidence that invariance-in...

0 Fanny Yang, et al. ∙

∙ 10/31/2017

Grouping-By-ID: Guarding Against Adversarial Domain Shifts

When training a deep network for image classification, one can broadly d...

0 Christina Heinze-Deml, et al. ∙

∙ 03/01/2017

Preserving Differential Privacy Between Features in Distributed Estimation

Privacy is crucial in many applications of machine learning. Legal, ethi...

0 Christina Heinze-Deml, et al. ∙

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