Search Results for author: Woonhyuk Baek

Found 5 papers, 2 papers with code

torchgpipe: On-the-fly Pipeline Parallelism for Training Giant Models

3 code implementations21 Apr 2020 Chiheon Kim, Heungsub Lee, Myungryong Jeong, Woonhyuk Baek, Boogeon Yoon, Ildoo Kim, Sungbin Lim, Sungwoong Kim

We design and implement a ready-to-use library in PyTorch for performing micro-batch pipeline parallelism with checkpointing proposed by GPipe (Huang et al., 2019).

Spatially Attentive Output Layer for Image Classification

no code implementations CVPR 2020 Ildoo Kim, Woonhyuk Baek, Sungwoong Kim

In this paper, we propose a novel spatial output layer on top of the existing convolutional feature maps to explicitly exploit the location-specific output information.

Classification General Classification +1

Scalable Neural Architecture Search for 3D Medical Image Segmentation

no code implementations13 Jun 2019 Sungwoong Kim, Ildoo Kim, Sungbin Lim, Woonhyuk Baek, Chiheon Kim, Hyungjoo Cho, Boogeon Yoon, Taesup Kim

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.

Image Segmentation Medical Image Segmentation +3

Cannot find the paper you are looking for? You can Submit a new open access paper.