25 citations · 139 across the 31 of their papers we have counts for
Showing 2017Show all
2 papers · 1 filter
stat.ML2017
Concept Formation and Dynamics of Repeated Inference in Deep Generative Models
Yoshihiro Nagano, Ryo Karakida, Masato Okada
Deep generative models are reported to be useful in broad applications including image generation. Repeated inference between data space and latent space in these models can denois…
stat.ML2017
Statistical Mechanics of Node-perturbation Learning with Noisy Baseline
Kazuyuki Hara, Kentaro Katahira, Masato Okada
Node-perturbation learning is a type of statistical gradient descent algorithm that can be applied to problems where the objective function is not explicitly formulated, including…