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2020 – today
- 2026
[c6]Thi Kieu Khanh Ho:
Time-Series Anomaly Detection with Graph-Based Self-Supervised Learning and Foundation Models: Towards Real-World Applications. AAAI 2026: 41054-41055- 2025
- [j6]Thi Kieu Khanh Ho
, Ali Karami, Narges Armanfard:
Graph Anomaly Detection in Time Series: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 47(8): 6990-7009 (2025) - [c5]Thi Kieu Khanh Ho, Narges Armanfard:
Contaminated Multivariate Time-Series Anomaly Detection with Spatio-Temporal Graph Conditional Diffusion Models. UAI 2025: 1710-1729 - [c4]Ali Karami, Thi Kieu Khanh Ho, Narges Armanfard:
Graph-Jigsaw Conditioned Diffusion Model for Skeleton-Based Video Anomaly Detection. WACV 2025: 4237-4247 - 2024
- [j5]Hadi Hojjati, Thi Kieu Khanh Ho, Narges Armanfard:
Self-supervised anomaly detection in computer vision and beyond: A survey and outlook. Neural Networks 172: 106106 (2024) - [c3]Thomas Lai, Thi Kieu Khanh Ho, Narges Armanfard:
Open-Set Multivariate Time-Series Anomaly Detection. ECAI 2024: 2003-2010 - [i6]Ali Karami, Thi Kieu Khanh Ho, Narges Armanfard:
Graph-Jigsaw Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection. CoRR abs/2403.12172 (2024) - 2023
- [c2]Thi Kieu Khanh Ho, Narges Armanfard:
Self-Supervised Learning for Anomalous Channel Detection in EEG Graphs: Application to Seizure Analysis. AAAI 2023: 7866-7874 - [i5]Thi Kieu Khanh Ho, Ali Karami, Narges Armanfard:
Graph-based Time-Series Anomaly Detection: A Survey. CoRR abs/2302.00058 (2023) - [i4]Thi Kieu Khanh Ho, Narges Armanfard:
Multivariate Time-Series Anomaly Detection with Contaminated Data: Application to Physiological Signals. CoRR abs/2308.12563 (2023) - [i3]Thomas Lai, Thi Kieu Khanh Ho, Narges Armanfard:
Open-Set Multivariate Time-Series Anomaly Detection. CoRR abs/2310.12294 (2023) - 2022
- [i2]Hadi Hojjati, Thi Kieu Khanh Ho, Narges Armanfard:
Self-Supervised Anomaly Detection: A Survey and Outlook. CoRR abs/2205.05173 (2022) - [i1]Thi Kieu Khanh Ho, Narges Armanfard:
Self-Supervised Learning for Anomalous Channel Detection in EEG Graphs: Application to Seizure Analysis. CoRR abs/2208.07448 (2022) - 2020
- [j4]Thi Kieu Khanh Ho, Jeonghwan Gwak:
Utilizing Knowledge Distillation in Deep Learning for Classification of Chest X-Ray Abnormalities. IEEE Access 8: 160749-160761 (2020) - [j3]Junho Ahn, Thi Kieu Khanh Ho, Jaeyong Kang, Jeonghwan Gwak:
Using Artificial Intelligence Methods for Dental Image Analysis: State-of-the-Art Reviews. J. Medical Imaging Health Informatics 10(11): 2532-2542 (2020)
2010 – 2019
- 2019
- [j2]Thi Kieu Khanh Ho, Jeonghwan Gwak, Chang Min Park, Jong-In Song:
Discrimination of Mental Workload Levels From Multi-Channel fNIRS Using Deep Leaning-Based Approaches. IEEE Access 7: 24392-24403 (2019) - [j1]Thi Kieu Khanh Ho, Jeonghwan Gwak:
Toward Deep Learning Approaches for Learning Structure Motifs and Classifying Biological Sequences From RNA A-to-I Editing Events. IEEE Access 7: 127464-127474 (2019) - [c1]Thi Kieu Khanh Ho, Jeonghwan Gwak, Om Prakash, Jong-In Song, Chang Min Park:
Utilizing Pretrained Deep Learning Models for Automated Pulmonary Tuberculosis Detection Using Chest Radiography. ACIIDS (2) 2019: 395-403
Coauthor Index
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