4 citations · 7 across the 3 of their papers we have counts for
3 papers
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.LG2022
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems
Hao Wang, Yifei Ma, Hao Ding +1
Recurrent neural networks have proven effective in modeling sequential user feedbacks for recommender systems. However, they usually focus solely on item relevance and fail to effe…
cs.LG2021★ 4 cited
Deep Explicit Duration Switching Models for Time Series
Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle +5
Many complex time series can be effectively subdivided into distinct regimes that exhibit persistent dynamics. Discovering the switching behavior and the statistical patterns in th…