Publications
ChainerMN: Scalable Distributed Deep Learning Framework
ML Systems Workshop in NIPS 2017
CuPy: A Numpy-compatible Library for NVIDIA GPU Calculations
ML Systems Workshop in NIPS 2017
Machine Learning / Deep Learning
By : Ryosuke Okuta, Yuya Unno, Daisuke Nishino, Shohei Hido, Crissman Loomis
Semi-supervised learning of hierarchical representations of molecules with neural message passing
Machine Learning for Molecules and Materials in NIPS 2017
Chemoinformatics / Materials Science
By : Hai Nguyen, Shin-ichi Maeda, Kenta Oono
Neural Sequence Model Training via α-divergence Minimization
Workshop on Learning to Generate Natural Language in ICML 2017
Machine Learning / Deep Learning
By : Sotetsu Koyamada, Yuta Kikuchi, Atsunori Kanemura, Shin-ichi Maeda, Shin Ishii
ICRA 2017 Workshop
FCN-Based 6D Robotic Grasping for Arbitrary Placed Objects
ICRA 2017 Workshop
By : Hitoshi Kusano, Ayaka Kume, Eiichi Matsumoto, Jethro Tan
Synthetic Gradient Methods with Virtual Forward-Backward Networks
ICLR2017 Workshop
Machine Learning / Deep Learning
By : Takeru Miyato, Daisuke Okanohara, Shin-ichi Maeda, Masanori Koyama
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
IEEE TPAMI
Machine Learning / Deep Learning
By : Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Shin Ishii
Distantly Supervised Road Segmentation
Workshop on Computer Vision for Road Scene Understanding and Autonomous Driving in ICCV 2017
By : Satoshi Tsutsui, Tommi Kerola, Shunta Saito
Evaluating the Variance of Likelihood-Ratio Gradient Estimators
ICML 2017
Machine Learning / Deep Learning
By : Seiya Tokui, Issei Sato
Learning Discrete Representations via Information Maximizing Self-Augmented Training
ICML 2017
Machine Learning / Deep Learning
By : Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama