Maximal margin learning vector quantisation. - Trung Le 001; Dat Tran 001; Van Nguyen 002; Wanli Ma (IJCNN, 2013)

Kernel-based semi-supervised learning for novelty detection. - Van Nguyen 002; Trung Le 001; Thien Pham; Mi Dinh; Thai Hoang Le (IJCNN, 2014)

Graph-based semi-supervised Support Vector Data Description for novelty detection. - Phuong Duong; Van Nguyen 002; Mi Dinh; Trung Le 001; Dat Tran 001; Wanli Ma (IJCNN, 2015)

Fast Kernel-based method for anomaly detection. - Anh Le; Trung Le 001; Khanh Nguyen; Van Nguyen 002; Thai Hoang Le; Dat Tran 001 (IJCNN, 2016)

Scalable Support Vector Machine for Semi-supervised Learning. - Trung Le 001; Khanh Nguyen; Van Nguyen 002; Vu Nguyen 001; Dinh Q. Phung (CoRR, 2016)

Jointly Predicting Affective and Mental Health Scores Using Deep Neural Networks of Visual Cues on the Web. - Hung Nguyen; Van Nguyen 002; Thin Nguyen; Mark E. Larsen; Bridianne O'Dea; Duc Thanh Nguyen; Trung Le 001; Dinh Q. Phung; Svetha Venkatesh; Helen Christensen (WISE (2), 2018)

Deep Domain Adaptation for Vulnerable Code Function Identification. - Van Nguyen 002; Trung Le 001; Tue Le; Khanh Nguyen; Olivier Y. DeVel; Paul Montague; Lizhen Qu; Dinh Q. Phung (IJCNN, 2019)

Code Pointer Network for Binary Function Scope Identification. - Van Nguyen 002; Trung Le 001; Tue Le; Khanh Nguyen; Olivier Y. de Vel; Paul Montague; Dinh Phung 001 (IJCNN, 2020)

Code Action Network for Binary Function Scope Identification. - Van Nguyen 002; Trung Le 001; Tue Le; Khanh Nguyen; Olivier Y. de Vel; Paul Montague; John C. Grundy; Dinh Phung 001 (PAKDD (1), 2020)

Dual-Component Deep Domain Adaptation: A New Approach for Cross Project Software Vulnerability Detection. - Van Nguyen 002; Trung Le 001; Olivier Y. de Vel; Paul Montague; John C. Grundy; Dinh Phung 001 (PAKDD (1), 2020)

Toward the Automated Construction of Probabilistic Knowledge Graphs for the Maritime Domain. - Fatemeh Shiri; Teresa Wang; Shirui Pan; Xiaojun Chang; Yuan-Fang Li; Reza Haffari; Van Nguyen 002; Shuang Yu (FUSION, 2021)

Information-theoretic Source Code Vulnerability Highlighting. - Van Nguyen 002; Trung Le 001; Olivier Y. de Vel; Paul Montague; John Grundy 001; Dinh Phung 001 (IJCNN, 2021)

Deep Learning for Software Security. - Van Nguyen 002 (2021)

Paraphrasing Techniques for Maritime QA system. - Fatemeh Shiri; Terry Yue Zhuo; Zhuang Li 001; Shirui Pan; Weiqing Wang 001; Reza Haffari; Yuan-Fang Li; Van Nguyen 002 (FUSION, 2022)

ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection. - Van-Anh Nguyen; Dai Quoc Nguyen; Van Nguyen 002; Trung Le 001; Quan Hung Tran; Dinh Phung 001 (ICSE-Companion, 2022)

VulRepair: a T5-based automated software vulnerability repair. - Michael Fu; Chakkrit Tantithamthavorn; Trung Le 001; Van Nguyen 002; Dinh Q. Phung (ESEC/SIGSOFT FSE, 2022)

Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation. - Tuan Nguyen 004; Van Nguyen 002; Trung Le 001; He Zhao 001; Quan Hung Tran; Dinh Q. Phung (UAI, 2022)

Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle. - Van Nguyen 002; Trung Le 001; Chakkrit Tantithamthavorn; John C. Grundy; Hung Nguyen; Dinh Q. Phung (CoRR, 2022)

An Information-Theoretic and Contrastive Learning-based Approach for Identifying Code Statements Causing Software Vulnerability. - Van Nguyen 002; Trung Le 001; Chakkrit Tantithamthavorn; John C. Grundy; Hung Nguyen; Seyit Camtepe; Paul Quirk; Dinh Q. Phung (CoRR, 2022)

Learning to Counter: Stochastic Feature-based Learning for Diverse Counterfactual Explanations. - Vy Vo; Trung Le 001; Van Nguyen 002; He Zhao 001; Edwin V. Bonilla; Gholamreza Haffari; Dinh Q. Phung (CoRR, 2022)

ChatGPT for Vulnerability Detection, Classification, and Repair: How Far Are We? - Michael Fu; Chakkrit Kla Tantithamthavorn; Van Nguyen 002; Trung Le 001 (APSEC, 2023)

Bounded Subjective Opinions. - Michael Kenneth McDonald; Lance M. Kaplan; Van Nguyen 002 (FUSION, 2023)

Few-shot Domain-Adaptative Visually-fused Event Detection from Text. - Farhad Moghimifar; Fatemeh Shiri; Reza Haffari; Yuan-Fang Li; Van Nguyen 002 (FUSION, 2023)

An Additive Instance-Wise Approach to Multi-class Model Interpretation. - Vy Vo; Van Nguyen 002; Trung Le 001; Quan Hung Tran; Gholamreza Haffari; Seyit Camtepe; Dinh Phung 001 (ICLR, 2023)

Theia: Weakly Supervised Multimodal Event Extraction from Incomplete Data. - Farhad Moghimifar; Fatemeh Shiri; Van Nguyen 002; Yuan-Fang Li; Gholamreza Haffari (IJCNLP (2), 2023)

Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations. - Vy Vo; Trung Le 001; Van Nguyen 002; He Zhao 001; Edwin V. Bonilla; Gholamreza Haffari; Dinh Q. Phung (KDD, 2023)

Few-shot Domain-Adaptive Visually-fused Event Detection from Text. - Fatemeh Shiri; Farhad Moghimifar; Van Nguyen 002; Reza Haffari; Yuan-Fang Li (CoRR, 2023)

Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities. - Michael Fu; Trung Le 001; Van Nguyen 002; Chakkrit Tantithamthavorn; Dinh Q. Phung (CoRR, 2023)

VulExplainer: A Transformer-Based Hierarchical Distillation for Explaining Vulnerability Types. - Michael Fu; Van Nguyen 002; Chakkrit Kla Tantithamthavorn; Trung Le 001; Dinh Q. Phung (IEEE Trans. Software Eng., 2023)

Decompose, Enrich, and Extract! Schema-aware Event Extraction using LLMs. - Fatemeh Shiri; Farhad Moghimifar; Reza Haffari; Yuan-Fang Li; Van Nguyen 002; John Yoo (FUSION, 2024)

Utilizing Large Language Models with Human Feedback Integration for Generating Dedicated Warning for Phishing Emails. - Quan Hong Nguyen; Tingmin Wu; Van Nguyen 002; Xingliang Yuan; Jason Xue 002; Carsten Rudolph (SecTL@AsiaCCS, 2024)

A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation. - Tuan Nguyen 004; Van Nguyen 002; Trung Le 001; He Zhao 001; Quan Hung Tran; Dinh Q. Phung (CoRR, 2024)

A Pioneering Study and An Innovative Information Theory-based Approach to Enhance The Transparency in Phishing Detection. - Van Nguyen 002; Tingmin Wu; Xingliang Yuan; Marthie Grobler; Surya Nepal; Carsten Rudolph (CoRR, 2024)

Deep Learning-Based Out-of-distribution Source Code Data Identification: How Far Have We Gone? - Van Nguyen 002; Xingliang Yuan; Tingmin Wu; Surya Nepal; Marthie Grobler; Carsten Rudolph (CoRR, 2024)

SAFE: Advancing Large Language Models in Leveraging Semantic and Syntactic Relationships for Software Vulnerability Detection. - Van Nguyen 002; Surya Nepal; Tingmin Wu; Xingliang Yuan; Carsten Rudolph (CoRR, 2024)

Adapting to Cyber Threats: A Phishing Evolution Network (PEN) Framework for Phishing Generation and Analyzing Evolution Patterns using Large Language Models. - Fengchao Chen; Tingmin Wu; Van Nguyen 002; Shuo Wang 012; Hongsheng Hu; Alsharif Abuadbba; Carsten Rudolph (CoRR, 2024)

AIBugHunter: A Practical tool for predicting, classifying and repairing software vulnerabilities. - Michael Fu; Chakkrit Tantithamthavorn; Trung Le 001; Yuki Kume; Van Nguyen 002; Dinh Q. Phung; John C. Grundy (Empir. Softw. Eng., 2024)

Vision Transformer Inspired Automated Vulnerability Repair. - Michael Fu; Van Nguyen 002; Chakkrit Tantithamthavorn; Dinh Phung 001; Trung Le 001 (ACM Trans. Softw. Eng. Methodol., 2024)

Deep Domain Adaptation With Max-Margin Principle for Cross-Project Imbalanced Software Vulnerability Detection. - Van Nguyen 002; Trung Le 001; Chakkrit Tantithamthavorn; John C. Grundy; Dinh Q. Phung (ACM Trans. Softw. Eng. Methodol., 2024)

AI2TALE: An Innovative Information Theory-based Approach for Learning to Localize Phishing Attacks. - Van Nguyen 002; Tingmin Wu; Xingliang Yuan; Marthie Grobler; Surya Nepal; Carsten Rudolph (ICLR, 2025)