Forward-Backward Smoothing for Hidden Markov Models of Point Pattern Data. - Nhan Dam; Dinh Q. Phung; Ba-Ngu Vo; Viet Huynh (DSAA, 2017)

Clustering Induced Kernel Learning. - Khanh Nguyen; Nhan Dam; Trung Le 001; Tu Dinh Nguyen; Dinh Q. Phung (ACML, 2018)

Model-based learning for point pattern data. - Ba-Ngu Vo; Nhan Dam; Dinh Q. Phung; Quang N. Tran; Ba-Tuong Vo (Pattern Recognit., 2018)

Three-Player Wasserstein GAN via Amortised Duality. - Nhan Dam; Quan Hoang; Trung Le 001; Tu Dinh Nguyen; Hung Bui 001; Dinh Phung 001 (IJCAI, 2019)

Explain by Evidence: An Explainable Memory-based Neural Network for Question Answering. - Quan Hung Tran; Nhan Dam; Tuan Manh Lai; Franck Dernoncourt; Trung Le 001; Nham Le; Dinh Phung 001 (COLING, 2020)

Scene Graph Modification Based on Natural Language Commands. - Xuanli He; Quan Hung Tran; Gholamreza Haffari; Walter Chang; Zhe Lin 001; Trung Bui; Franck Dernoncourt; Nhan Dam (EMNLP (Findings), 2020)

Stein Variational Gradient Descent with Variance Reduction. - Nhan Dam; Trung Le 001; Viet Huynh; Dinh Phung 001 (IJCNN, 2020)

TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport. - Tuan Nguyen 004; Trung Le 001; Nhan Dam; Quan Hung Tran; Truyen Nguyen; Dinh Q. Phung (IJCAI, 2021)

On efficient multilevel Clustering via Wasserstein distances. - Viet Huynh; Nhat Ho; Nhan Dam; XuanLong Nguyen; Mikhail Yurochkin; Hung Bui 001; Dinh Q. Phung (J. Mach. Learn. Res., 2021)