12 citations · 12 across the 1 of their papers we have counts for
4 papers
NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity
Sang-gil Lee, Sungwon Kim, Sungroh Yoon
Normalizing flows (NFs) have become a prominent method for deep generative models that allow for an analytic probability density estimation and efficient synthesis. However, a flow…
One-Shot Learning for Text-to-SQL Generation
Dongjun Lee, Jaesik Yoon, Jongyun Song +2
Most deep learning approaches for text-to-SQL generation are limited to the WikiSQL dataset, which only supports very simple queries. Recently, template-based and sequence-to-seque…
FloWaveNet : A Generative Flow for Raw Audio
Sungwon Kim, Sang-gil Lee, Jongyoon Song +2
Most modern text-to-speech architectures use a WaveNet vocoder for synthesizing high-fidelity waveform audio, but there have been limitations, such as high inference time, in its p…
Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector
Sang-gil Lee, Jae Seok Bae, Hyunjae Kim +2
We present a focal liver lesion detection model leveraged by custom-designed multi-phase computed tomography (CT) volumes, which reflects real-world clinical lesion detection pract…