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stat.ML2024
Scaling-based Data Augmentation for Generative Models and its Theoretical Extension
Yoshitaka Koike, Takumi Nakagawa, Hiroki Waida +1
This paper studies stable learning methods for generative models that enable high-quality data generation. Noise injection is commonly used to stabilize learning. However, selectin…
stat.ML2024
Investigating Self-Supervised Image Denoising with Denaturation
Hiroki Waida, Kimihiro Yamazaki, Atsushi Tokuhisa +2
Self-supervised learning for image denoising problems in the presence of denaturation for noisy data is a crucial approach in machine learning. However, theoretical understanding o…