25 citations · 87 across the 15 of their papers we have counts for
5 papers · 1 filter
Hierarchical Self-Supervised Representation Learning Framework for Multivariate Time Series Grounded in ECG Analysis
Siwon Kim
Data analysis in the medical domain often encounters scenarios involving a limited target dataset and a large, unannotated dataset with a general distribution. Under such circumsta…
Battling the Non-stationarity in Time Series Forecasting via Test-time Adaptation
HyunGi Kim, Siwon Kim, Jisoo Mok +1
Deep Neural Networks have spearheaded remarkable advancements in time series forecasting (TSF), one of the major tasks in time series modeling. Nonetheless, the non-stationarity of…
Probabilistic Concept Bottleneck Models
Eunji Kim, Dahuin Jung, Sangha Park +2
Interpretable models are designed to make decisions in a human-interpretable manner. Representatively, Concept Bottleneck Models (CBM) follow a two-step process of concept predicti…
On the Impact of Knowledge Distillation for Model Interpretability
Hyeongrok Han, Siwon Kim, Hyun-Soo Choi +1
Several recent studies have elucidated why knowledge distillation (KD) improves model performance. However, few have researched the other advantages of KD in addition to its improv…
Towards a Rigorous Evaluation of Time-series Anomaly Detection
Siwon Kim, Kukjin Choi, Hyun-Soo Choi +2
In recent years, proposed studies on time-series anomaly detection (TAD) report high F1 scores on benchmark TAD datasets, giving the impression of clear improvements in TAD. Howeve…