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Kenta Oono

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Minimax statistical learning with Wasserstein distances (NeurIPS2018 Reading Club)
byKenta Oono
 
Deep learning for molecules, introduction to chainer chemistry
byKenta Oono
 
Overview of Machine Learning for Molecules and Materials Workshop @ NIPS2017
byKenta Oono
 
Comparison of deep learning frameworks from a viewpoint of double backpropagation
byKenta Oono
 
深層学習フレームワーク概要とChainerの事例紹介
byKenta Oono
 
20170422 数学カフェ Part2
byKenta Oono
 
20170422 数学カフェ Part1
byKenta Oono
 
情報幾何学の基礎、第7章発表ノート
byKenta Oono
 
GTC Japan 2016 Chainer feature introduction
byKenta Oono
 
On the benchmark of Chainer
byKenta Oono
 
Tokyo Webmining Talk1
byKenta Oono
 
VAE-type Deep Generative Models
byKenta Oono
 
Common Design of Deep Learning Frameworks
byKenta Oono
 
Introduction to Chainer and CuPy
byKenta Oono