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Pedro G. Lind

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#artificial intelligence Preprint Sep 2026

Diffusion models for eye-gaze trajectory generation using position and velocity representations

Eye-tracking data are expensive to collect, requiring specialized hardware and controlled laboratory conditions, and difficult to share because of privacy constraints. We address this using two complementary denoising diffusion probabilistic models (DDPMs) for unconditional generation of eye-gaze dynamics from visual-s...

Laxman Basnet, Alexander Szorkovszky, Pedro G. Lind et al. · 0 citations

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