1 citations · 1 across the 4 of their papers we have counts for
4 papers
Hawkes Process Based on Controlled Differential Equations
Minju Jo, Seungji Kook, Noseong Park
Hawkes processes are a popular framework to model the occurrence of sequential events, i.e., occurrence dynamics, in several fields such as social diffusion. In real-world scenario…
Learnable Path in Neural Controlled Differential Equations
Sheo Yon Jhin, Minju Jo, Seungji Kook +3
Neural controlled differential equations (NCDEs), which are continuous analogues to recurrent neural networks (RNNs), are a specialized model in (irregular) time-series processing.…
TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering
Seoyoung Hong, Minju Jo, Seungji Kook +4
Recommender systems are a long-standing research problem in data mining and machine learning. They are incremental in nature, as new user-item interaction logs arrive. In real-worl…
EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting
Sheo Yon Jhin, Jaehoon Lee, Minju Jo +5
Deep learning inspired by differential equations is a recent research trend and has marked the state of the art performance for many machine learning tasks. Among them, time-series…