550 citations · 718 across the 45 of their papers we have counts for
6 papers · 1 filter
MadSGM: Multivariate Anomaly Detection with Score-based Generative Models
Haksoo Lim, Sewon Park, Minjung Kim +3
The time-series anomaly detection is one of the most fundamental tasks for time-series. Unlike the time-series forecasting and classification, the time-series anomaly detection typ…
Precursor-of-Anomaly Detection for Irregular Time Series
Sheo Yon Jhin, Jaehoon Lee, Noseong Park
Anomaly detection is an important field that aims to identify unexpected patterns or data points, and it is closely related to many real-world problems, particularly to application…
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…
CoDi: Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis
Chaejeong Lee, Jayoung Kim, Noseong Park
With growing attention to tabular data these days, the attempt to apply a synthetic table to various tasks has been expanded toward various scenarios. Owing to the recent advances…
Graph Neural Rough Differential Equations for Traffic Forecasting
Jeongwhan Choi, Noseong Park
Traffic forecasting is one of the most popular spatio-temporal tasks in the field of machine learning. A prevalent approach in the field is to combine graph convolutional networks…
Regular Time-series Generation using SGM
Haksoo Lim, Minjung Kim, Sewon Park +1
Score-based generative models (SGMs) are generative models that are in the spotlight these days. Time-series frequently occurs in our daily life, e.g., stock data, climate data, an…