5 citations · 9 across the 8 of their papers we have counts for
5 papers · 1 filter
CF-JEPA: Mask-free forward prediction with asymmetric encoder utilization for time-series representation learning
Jaehoon Lee, Sunghyun Sim
Self-supervised learning (SSL) for time-series representation learning is dominated by two paradigms: contrastive methods, which face challenges in constructing positive or negativ…
FEATHer: Fourier-Efficient Adaptive Temporal Hierarchy Forecaster for Time-Series Forecasting
Jaehoon Lee, Seungwoo Lee, Younghwi Kim +2
Time-series forecasting is fundamental in industrial domains like manufacturing and smart factories. As systems evolve toward automation, models must operate on edge devices (e.g.,…
Distributed Lag Transformer based on Time-Variable-Aware Learning for Explainable Multivariate Time Series Forecasting
Younghwi Kim, Dohee Kim, Joongrock Kim +1
Time series data is a key element of big data analytics, commonly found in domains such as finance, healthcare, climate forecasting, and transportation. In large scale real world s…
Automatic Discovery of Multi-perspective Process Model using Reinforcement Learning
Sunghyun Sim, Ling Liu, Hyerim Bae
Process mining is a methodology for the derivation and analysis of process models based on the event log. When process mining is employed to analyze business processes, the process…
Correlation recurrent units: A novel neural architecture for improving the predictive performance of time-series data
Sunghyun Sim, Dohee Kim, Hyerim Bae
The time-series forecasting (TSF) problem is a traditional problem in the field of artificial intelligence. Models such as Recurrent Neural Network (RNN), Long Short Term Memory (L…