Discord Detection in Streaming Time Series with the Support of R-Tree. - Pham Minh Chau 001; Bui Minh Duc; Duong Tuan Anh (ACOMP, 2018)

Discord Discovery in Streaming Time Series based on an Improved HOT SAX Algorithm. - Pham Minh Chau 001; Bui Minh Duc; Duong Tuan Anh (SoICT, 2018)

Solar Flare Prediction Using Two-tier Ensemble with Deep Learning and Gradient Boosting Machine. - Chau Pham 001; Vung Pham; Tommy Dang (IEEE BigData, 2019)

Graph Adversarial Attacks and Defense: An Empirical Study on Citation Graph. - Chau Pham 001; Vung Pham; Tommy Dang (IEEE BigData, 2020)

Road Damage Detection and Classification with Detectron2 and Faster R-CNN. - Vung Pham; Chau Pham 001; Tommy Dang (IEEE BigData, 2020)

GenExplorer: Visualizing and Comparing Gene Expression Levels via Differential Charts. - Chau Pham 001; Vung Pham; Tommy Dang (ISVC (1), 2020)

SkeletonVR: Educating Human Anatomy Through An Interactive Puzzle Assembly. - Jake Gonzalez; Chau Pham 001; Afamefuna Umejiaku; Juanita Benjamin; Tommy Dang (IAIT, 2021)

Link Prediction for Biomedical Network. - Chau Pham 001; Tommy Dang (IAIT, 2021)

A Multi-scale Graph Signature for Persistence Diagrams based on Return Probabilities of Random Walks. - Chau Pham 001; Trung Dang 002; Peter Chin 001 (CoRR, 2022)

Deep Distance Sensitivity Oracles. - Davin Jeong; Chau Pham 001; Arnav Bhakta; Sarel Cohen; Maximilian Katzmann; Tobias Friedrich 001; Sang (Peter) Chin (CoRR, 2022)

Deep Distance Sensitivity Oracles. - Davin Jeong; Allison Gunby-Mann; Sarel Cohen; Maximilian Katzmann; Chau Pham 001; Arnav Bhakta; Tobias Friedrich 001; Peter Chin 001 (COMPLEX NETWORKS (1), 2023)

CHAMMI: A benchmark for channel-adaptive models in microscopy imaging. - Zitong Sam Chen; Chau Pham 001; Siqi Wang; Michael Doron; Nikita Moshkov; Bryan A. Plummer; Juan C. Caicedo (NeurIPS, 2023)

A Unified Framework for Connecting Noise Modeling to Boost Noise Detection. - Siqi Wang; Chau Pham 001; Bryan A. Plummer (CoRR, 2023)

Let Models Speak Ciphers: Multiagent Debate through Embeddings. - Chau Pham 001; Boyi Liu 001; Yingxiang Yang; Zhengyu Chen 001; Tianyi Liu; Jianbo Yuan; Bryan A. Plummer; Zhaoran Wang 001; Hongxia Yang (ICLR, 2024)

MixtureGrowth: Growing Neural Networks by Recombining Learned Parameters. - Chau Pham 001; Piotr Teterwak; Soren Nelson; Bryan A. Plummer (WACV, 2024)

Enhancing Feature Diversity Boosts Channel-Adaptive Vision Transformers. - Chau Pham 001; Bryan A. Plummer (CoRR, 2024)

ChA-MAEViT: Unifying Channel-Aware Masked Autoencoders and Multi-Channel Vision Transformers for Improved Cross-Channel Learning. - Chau Pham 001; Juan C. Caicedo; Bryan A. Plummer (CoRR, 2025)