3 papers
stat.ML2025
Continuum Dropout for Neural Differential Equations
Jonghun Lee, YongKyung Oh, Sungil Kim +1
Neural Differential Equations (NDEs) excel at modeling continuous-time dynamics, effectively handling challenges such as irregular observations, missing values, and noise. Despite…
cs.LG2025
Modeling Irregular Astronomical Time Series with Neural Stochastic Delay Differential Equations
YongKyung Oh, Seungsu Kam, Dong-Young Lim +1
Astronomical time series from large-scale surveys like LSST are often irregularly sampled and incomplete, posing challenges for classification and anomaly detection. We introduce a…
cs.LG2025
Comprehensive Review of Neural Differential Equations for Time Series Analysis
YongKyung Oh, Seungsu Kam, Jonghun Lee +3
Time series modeling and analysis have become critical in various domains. Conventional methods such as RNNs and Transformers, while effective for discrete-time and regularly sampl…