Christina Heinze-Deml

According to our database, Christina Heinze-Deml authored at least 15 papers between 2015 and 2026.

Collaborative distances:

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

2026

Anti-causal domain generalization: Leveraging unlabeled data.

Sorawit Saengkyongam, Juan L. Gamella, Andrew C. Miller, Jonas Peters, Nicolai Meinshausen, Christina Heinze-Deml

CoRR, February, 2026

2025

Hybrid Modeling of Photoplethysmography for Non-invasive Monitoring of Cardiovascular Parameters.

Emanuele Palumbo, Sorawit Saengkyongam, Maria R. Cervera, Jens Behrmann, Andrew C. Miller, Guillermo Sapiro, Christina Heinze-Deml, Antoine Wehenkel

CoRR, November, 2025

Do LLMs estimate uncertainty well in instruction-following?

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Do LLMs "know" internally when they follow instructions?

Juyeon Heo, Christina Heinze-Deml, Oussama Elachqar, Kwan Ho Ryan Chan, Shirley You Ren, Andrew C. Miller, Udhyakumar Nallasamy, Jaya Narain

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Learning and scoring Gaussian latent variable causal models with unknown additive interventions.

Armeen Taeb, Juan L. Gamella, Christina Heinze-Deml, Peter Bühlmann

J. Mach. Learn. Res., 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 "know" internally when they follow instructions?

Juyeon Heo, Christina Heinze-Deml, Oussama Elachqar, Shirley You 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 L. 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