101 citations · 139 across the 6 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2022★ 3 cited
Robust Probabilistic Time Series Forecasting
TaeHo Yoon, Youngsuk Park, Ernest K. Ryu +1
Probabilistic time series forecasting has played critical role in decision-making processes due to its capability to quantify uncertainties. Deep forecasting models, however, could…
cs.LG2021
WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points
Albert No, TaeHo Yoon, Sehyun Kwon +1
Generative adversarial networks (GAN) are a widely used class of deep generative models, but their minimax training dynamics are not understood very well. In this work, we show tha…
cs.LG2019
ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems
Ernest K. Ryu, Kun Yuan, Wotao Yin
Despite remarkable empirical success, the training dynamics of generative adversarial networks (GAN), which involves solving a minimax game using stochastic gradients, is still poo…