284 citations · 921 across the 16 of their papers we have counts for
4 papers · 1 filter
Variational Temporal Abstraction
Taesup Kim, Sungjin Ahn, Yoshua Bengio
We introduce a variational approach to learning and inference of temporally hierarchical structure and representation for sequential data. We propose the Variational Temporal Abstr…
Scalable Neural Architecture Search for 3D Medical Image Segmentation
Sungwoong Kim, Ildoo Kim, Sungbin Lim +5
In this paper, a neural architecture search (NAS) framework is proposed for 3D medical image segmentation, to automatically optimize a neural architecture from a large design space…
Fast AutoAugment
Sungbin Lim, Ildoo Kim, Taesup Kim +2
Data augmentation is an essential technique for improving generalization ability of deep learning models. Recently, AutoAugment has been proposed as an algorithm to automatically s…
Edge-labeling Graph Neural Network for Few-shot Learning
Jongmin Kim, Taesup Kim, Sungwoong Kim +1
In this paper, we propose a novel edge-labeling graph neural network (EGNN), which adapts a deep neural network on the edge-labeling graph, for few-shot learning. The previous grap…