Tuan L. Vo

According to our database, Tuan L. Vo authored at least 12 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

PICA: Interpretable imputation for randomly missing data.

Tuan L. Vo, Uyen Dang, Van Hua, Xuan Hoang Nguyen, Thu Nguyen, Bao Huynh

Inf. Sci., 2026

Explainability of machine learning models under missing data.

Tuan L. Vo, Thu Nguyen, Luis M. Lopez-Ramos, Hugo Lewi Hammer, Michael A. Riegler, Pål Halvorsen

Appl. Soft Comput., 2026

Contrastive Integrated Gradients: A Feature Attribution-Based Method for Explaining Whole Slide Image Classification.

Anh Mai Vu, Tuan L. Vo, Ngoc Lam Quang Bui, Nam N. B. Le, Akash Awasthi, Huy Quoc Vo, Thanh-Huy Nguyen, Zhu Han, Chandra Mohan, Hien Van Nguyen

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2026

DPERC: Direct Parameter Estimation for Mixed Data with Random Missingness.

Tuan L. Vo, Uyen Dang, Thu Nguyen, Pål Halvorsen, Michael A. Riegler, Binh T. Nguyen

Proceedings of the MultiMedia Modeling, 2026

2025

Contrastive Integrated Gradients: A Feature Attribution-Based Method for Explaining Whole Slide Image Classification.

Anh Mai Vu, Tuan L. Vo, Ngoc Lam Quang Bui, Nam Nguyen Le Binh, Akash Awasthi, Huy Quoc Vo, Thanh-Huy Nguyen, Zhu Han, Chandra Mohan, Hien Van Nguyen

CoRR, November, 2025

DPERC: Direct Parameter Estimation for Mixed Data.

Tuan L. Vo, Quan Huu Do, Uyen Dang, Thu Nguyen, Pål Halvorsen, Michael A. Riegler, Binh T. Nguyen

CoRR, January, 2025

Imputation Using Training Labels and Classification via Label Imputation.

Thu Nguyen, Uyen Dang, Tuan L. Vo, Pål Halvorsen, Michael A. Riegler

IEEE Access, 2025

Emotion Recognition Using Text Embedding Models: Wearable and Wireless EEG Without Fixed EEG Channel Configurations.

Quoc-Toan Nguyen, Huiru Zheng, Tahia Tazin, Linh Le, Tuan L. Vo, Nhu-Tri Tran, David Williams-King, Benjamin Tag

Proceedings of the Adjunct Proceedings of the 33rd ACM Conference on User Modeling, 2025

2024

Weighted Missing Linear Discriminant Analysis: An Explainable Approach for Classification with Missing Data.

Tuan L. Vo, Uyen Dang, Thu Nguyen

CoRR, 2024

Explainability of Machine Learning Models under Missing Data.

Tuan L. Vo, Thu Nguyen, Hugo Lewi Hammer, Michael A. Riegler, Pål Halvorsen

CoRR, 2024

The Effects of Data Imputation on Covariance and Inverse Covariance Matrix Estimation.

Tuan L. Vo, Quan Huu Do, Thu Nguyen, Pål Halvorsen, Michael A. Riegler, Binh T. Nguyen

IEEE Access, 2024

Blockwise Principal Component Analysis for monotone missing data imputation and dimensionality reduction.

Tu T. Do, Anh M. Vu, Tuan L. Vo, Hoang Thien Ly, Thu Nguyen, Steven Hicks, Pål Halvorsen, Michael Riegler, Binh T. Nguyen

Proceedings of the International Joint Conference on Neural Networks, 2024