Christina Heinze-Deml

According to our database, Christina Heinze-Deml authored at least 11 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Considerations for Distribution Shift Robustness of Diagnostic Models in Healthcare.

Arno Blaas, Adam Golinski, Andrew C. Miller, Luca Zappella, Jörn-Henrik Jacobsen, Christina Heinze-Deml

CoRR, 2024

Do LLMs estimate uncertainty well in instruction-following?

Juyeon Heo, Miao Xiong, Christina Heinze-Deml, Jaya Narain

CoRR, 2024

Do LLMs "know" internally when they follow instructions?

Juyeon Heo, Christina Heinze-Deml, Oussama Elachqar, Shirley Ren, Udhay Nallasamy, Andy Miller, Kwan Ho Ryan Chan, Jaya Narain

CoRR, 2024

2021

Conditional variance penalties and domain shift robustness.

Christina Heinze-Deml, Nicolai Meinshausen

Mach. Learn., 2021

2020

Think before you act: A simple baseline for compositional generalization.

Christina Heinze-Deml, Diane Bouchacourt

CoRR, 2020

Active Invariant Causal Prediction: Experiment Selection through Stability.

Juan Gamella, Christina Heinze-Deml

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

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

Fanny Yang, Zuowen Wang, Christina Heinze-Deml

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2017

Guarding Against Adversarial Domain Shifts with Counterfactual Regularization.

Christina Heinze-Deml, Nicolai Meinshausen

CoRR, 2017

Preserving Differential Privacy Between Features in Distributed Estimation.

Christina Heinze-Deml, Brian McWilliams, Nicolai Meinshausen

CoRR, 2017

2016

DUAL-LOCO: Distributing Statistical Estimation Using Random Projections.

Christina Heinze, Brian McWilliams, Nicolai Meinshausen

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions.

Dominik Rothenhäusler, Christina Heinze, Jonas Peters, Nicolai Meinshausen

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015