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Nathan Stromberg

3 accepted papers

2025

CORAL: Disentangling Latent Representations in Long-Tailed Diffusion

NeurIPS 2025poster

Diffusion models have achieved impressive performance in generating high-quality and diverse synthetic data. However, their success typically assumes a class-balanced training distribution. In real-world settings, multi-class data often follow a long-tailed distribution, where standard diffusion mod…

Cited by 0SourceScholar
2025

Thumb on the Scale: Optimal Loss Weighting in Last Layer Retraining

NeurIPS 2025poster

While machine learning models become more capable in discriminative tasks at scale, their ability to overcome biases introduced by training data has come under increasing scrutiny. Previous results suggest that there are two extremes of parameterization with very different behaviors: the population…

Cited by 0SourceScholar
2024

Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections

NeurIPS 2024poster

Last-layer retraining methods have emerged as an efficient framework for correcting existing base models. Within this framework, several methods have been proposed to deal with correcting models for subgroup fairness with and without group membership information. Importantly, prior work has demonstr…

Cited by 1SourcePDFScholar