46 citations · 149 across the 11 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2020★ 4 cited
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…
cs.LG2016★ 1 cited
An Efficient Approach to Boosting Performance of Deep Spiking Network Training
Seongsik Park, Sang-gil Lee, Hyunha Nam +1
Nowadays deep learning is dominating the field of machine learning with state-of-the-art performance in various application areas. Recently, spiking neural networks (SNNs) have bee…