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cs.LG2019★ 34 cited
High-Quality Self-Supervised Deep Image Denoising
Samuli Laine, Tero Karras, Jaakko Lehtinen +1
We describe a novel method for training high-quality image denoising models based on unorganized collections of corrupted images. The training does not need access to clean referen…
cs.LG2018
PPO-CMA: Proximal Policy Optimization with Covariance Matrix Adaptation
Perttu Hämäläinen, Amin Babadi, Xiaoxiao Ma +1
Proximal Policy Optimization (PPO) is a highly popular model-free reinforcement learning (RL) approach. However, we observe that in a continuous action space, PPO can prematurely s…