Nina Weng

According to our database, Nina Weng authored at least 14 papers between 2020 and 2026.

Collaborative distances:

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

2026

Detecting labeling bias using influence functions.

Frida Jørgensen, Nina Weng, Siavash Arjomand Bigdeli

CoRR, February, 2026

2025

Weight Space Correlation Analysis: Quantifying Feature Utilization in Deep Learning Models.

Chun Kit Wong, Paraskevas Pegios, Nina Weng, Emilie Pi Fogtmann Sejer, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen

CoRR, December, 2025

Patronus: Bringing Transparency to Diffusion Models with Prototypes.

Nina Weng, Aasa Feragen, Siavash Arjomand Bigdeli

CoRR, March, 2025

Diffusion-Based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment.

Paraskevas Pegios, Manxi Lin, Nina Weng, Morten Bo Søndergaard Svendsen, Zahra Bashir, Siavash Arjomand Bigdeli, Anders Nymark Christensen, Martin Grønnebæk Tolsgaard, Aasa Feragen

Proceedings of the Simplifying Medical Ultrasound - 6th International Workshop, 2025

In the Picture: Medical Imaging Datasets, Artifacts, and their Living Review.

Amelia Jiménez-Sánchez, Natalia Rozalia Avlona, Sarah de Boer, Víctor M. Campello, Aasa Feragen, Enzo Ferrante, Melanie Ganz, Judy Wawira Gichoya, Camila González, Steff Groefsema, Alessa Hering, Adam Hulman, Leo Joskowicz, Dovile Juodelyte, Melih Kandemir, Thijs Kooi, Jorge del Pozo Lérida, Livie Yumeng Li, André G. C. Pacheco, Tim Rädsch, Mauricio Reyes, Théo Sourget, Bram van Ginneken, David Wen, Nina Weng, Jack Junchi Xu, Hubert Dariusz Zajac, Maria A. Zuluaga, Veronika Cheplygina

Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

2024

Non-discrimination Criteria for Generative Language Models.

Sara Sterlie, Nina Weng, Aasa Feragen

CoRR, 2024

Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis Using Slice Discovery Methods.

Vincent Olesen, Nina Weng, Aasa Feragen, Eike Petersen

Proceedings of the Ethics and Fairness in Medical Imaging, 2024

Shortcut Learning in Medical Image Segmentation.

Manxi Lin, Nina Weng, Kamil Wojciech Mikolaj, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Fast Diffusion-Based Counterfactuals for Shortcut Removal and Generation.

Nina Weng, Paraskevas Pegios, Eike Petersen, Aasa Feragen, Siavash Arjomand Bigdeli

Proceedings of the Computer Vision - ECCV 2024, 2024

Generalizing Fairness to Generative Language Models via Reformulation of Non-discrimination Criteria.

Sara Sterlie, Nina Weng, Aasa Feragen

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

2023

An Interpretable and Attention-Based Method for Gaze Estimation Using Electroencephalography.

Nina Weng, Martyna Plomecka, Manuel Kaufmann, Ard Kastrati, Roger Wattenhofer, Nicolas Langer

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Are Sex-Based Physiological Differences the Cause of Gender Bias for Chest X-Ray Diagnosis?

Nina Weng, Siavash Arjomand Bigdeli, Eike Petersen, Aasa Feragen

Proceedings of the Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging, 2023

2022

Will You Ever Become Popular? Learning to Predict Virality of Dance Clips.

Jiahao Wang, Yunhong Wang, Nina Weng, Tianrui Chai, Annan Li, Faxi Zhang, Sansi Yu

ACM Trans. Multim. Comput. Commun. Appl., 2022

2020

Two-Stream Temporal Convolutional Network for Dynamic Facial Attractiveness Prediction.

Nina Weng, Jiahao Wang, Annan Li, Yunhong Wang

Proceedings of the 25th International Conference on Pattern Recognition, 2020