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Posts by Collection
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publications
How I Met Your Bias: Investigating Bias Amplification in Diffusion Models
Published in 2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2026
Nathan Roos, Ani Gjergji, Ekaterina Iakovleva, Vito Paolo Pastore and Enzo Tartaglione
For the first time, we show that sampling hyperparameters influence bias amplification in diffusion models during the inference process, across sampling algorithms, datasets, and model architectures.
Data-Driven Soft Labeling Scales DNA Read Classification to Whole-Body Cell-Type Deconvolution
Published in 40th Conference on Neural Information Processing Systems (NeurIPS 2026), 2026
Dmytro Rizdvanetskyi, Nathan Roos, Pavlo Lutsik
We propose data-driven soft labels that estimate the conditional cell-type distribution for each read DNA, and integrate this scheme into Syto, a new modular framework for read-level classification-based cell-type deconvolution.
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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