Hua Mao

55 papers A* 4A 1B 1C 1Journal 37Unranked 11
YearRankTypeTitle / Venue / Authors
2026 A* conf
Conditional Distribution Learning for Graph Classification.
AAAI
Jie Chen, Hua Mao, Chuanbin Liu, Zhu Wang, Xi Peng
2026 J jnl
GradCFA: A Hybrid Gradient-Based Counterfactual and Feature Attribution Explanation Algorithm for Local Interpretation of Neural Networks.
CoRR
Jacob Sanderson, Hua Mao, Wai Lok Woo
2026 J jnl
Homophilic-aware graph contrastive learning.
Pattern Recognit.
Li Zhang, Hua Mao, Wai Lok Woo, Jie Chen
2025 A* conf
Cross-View Graph Consistency Learning for Invariant Graph Representations.
AAAI
Jie Chen, Hua Mao, Wai Lok Woo, Chuanbin Liu, Xi Peng
2025 — conf
DiPACE: Diverse, Plausible and Actionable Counterfactual Explanations.
ICAART (2)
Jacob Sanderson, Hua Mao, Wai Lok Woo
2025 J jnl
Efficient algorithms for collecting the statistics of large-scale IP address data.
Comput. Sci. Inf. Syst.
Hui Liu, Yi Cao, Zehan Cai, Hua Mao, Jie Chen
2025 J jnl
GradCFA: A Hybrid Gradient-Based Counterfactual and Feature Attribution Explanation Algorithm for Local Interpretation of Neural Networks.
IEEE Trans. Artif. Intell.
Jacob Sanderson, Hua Mao, Wai Lok Woo
2025 J jnl
Hierarchical Sparse Representation Clustering for High-Dimensional Data Streams.
IEEE Trans. Neural Networks Learn. Syst.
Jie Chen, Hua Mao, Yuanbiao Gou, Xi Peng
2025 J jnl
One-Step Adaptive Graph Learning for Incomplete Multiview Subspace Clustering.
IEEE Trans. Knowl. Data Eng.
Jie Chen, Hua Mao, Wai Lok Woo, Chuanbin Liu, Zhu Wang, Xi Peng
2025 J jnl
Progressive low-confidence pseudolabeling for semisupervised node classification.
Neurocomputing
Tao Zhu, Hua Mao, Hui Liu, Jie Chen
2024 J jnl
Dynamic Graph Embedding via Meta-Learning.
IEEE Trans. Knowl. Data Eng.
Yuren Mao, Yu Hao, Xin Cao, Yixiang Fang, Xuemin Lin, Hua Mao, Zhiqiang Xu
2024 J jnl
Explainable AI Evaluation: A Top-Down Approach for Selecting Optimal Explanations for Black Box Models.
Inf.
Seyedeh Roksana Mirzaei, Hua Mao, Raid Rafi Omar Al-Nima, Wai Lok Woo
2024 — conf
Explainable Deep Semantic Segmentation for Flood Inundation Mapping with Class Activation Mapping Techniques.
ICAART (3)
Jacob Sanderson, Hua Mao, Naruephorn Tengtrairat, Raid Rafi Omar Al-Nima, Wai Lok Woo
2024 J jnl
Hierarchical Sparse Representation Clustering for High-Dimensional Data Streams.
CoRR
Jie Chen, Hua Mao, Yuanbiao Gou, Xi Peng
2024 J jnl
Self-Supervised Conditional Distribution Learning on Graphs.
CoRR
Jie Chen, Hua Mao, Yuanbiao Gou, Zhu Wang, Xi Peng
2023 J jnl
Cross-View Graph Consistency Learning for Invariant Graph Representations.
CoRR
Jie Chen, Zhiming Li, Hua Mao, Wai Lok Woo, Xi Peng
2023 A* conf
Deep Multiview Clustering by Contrasting Cluster Assignments.
ICCV
Jie Chen, Hua Mao, Wai Lok Woo, Xi Peng
2023 J jnl
Deep Multiview Clustering by Contrasting Cluster Assignments.
CoRR
Jie Chen, Hua Mao, Wai Lok Woo, Xi Peng
2023 J jnl
Efficient Sparse Representation for Learning With High-Dimensional Data.
IEEE Trans. Neural Networks Learn. Syst.
Jie Chen, Shengxiang Yang, Zhu Wang, Hua Mao
2023 J jnl
Low-Rank Tensor Learning for Incomplete Multiview Clustering.
IEEE Trans. Knowl. Data Eng.
Jie Chen, Zhu Wang, Hua Mao, Xi Peng
2023 J jnl
Multiview Clustering by Consensus Spectral Rotation Fusion.
IEEE Trans. Image Process.
Jie Chen, Hua Mao, Dezhong Peng, Changqing Zhang, Xi Peng
2023 J jnl
Optimal Fusion of Multispectral Optical and SAR Images for Flood Inundation Mapping through Explainable Deep Learning.
Inf.
Jacob Sanderson, Hua Mao, Mohammed A. M. Abdullah, Raid Rafi Omar Al-Nima, Wai Lok Woo
2023 J jnl
Two-Stage Sparse Representation Clustering for Dynamic Data Streams.
IEEE Trans. Cybern.
Jie Chen, Zhu Wang, Shengxiang Yang, Hua Mao
2022 J jnl
Multiview Subspace Clustering Using Low-Rank Representation.
IEEE Trans. Cybern.
Jie Chen, Shengxiang Yang, Hua Mao, Conor Fahy
2022 J jnl
Subtraction Gates: Another Way to Learn Long-Term Dependencies in Recurrent Neural Networks.
IEEE Trans. Neural Networks Learn. Syst.
Tao He, Hua Mao, Zhang Yi
2021 J jnl
Efficient algorithms for collecting the statistics of large-scale IP address data.
CoRR
Jie Chen, Hua Mao
2021 J jnl
Low-rank representation with adaptive dictionary learning for subspace clustering.
Knowl. Based Syst.
Jie Chen, Hua Mao, Zhu Wang, Xinpei Zhang
2019 J jnl
Spectrogram based multi-task audio classification.
Multim. Tools Appl.
Yuni Zeng, Hua Mao, Dezhong Peng, Zhang Yi
2019 J jnl
Stem cell motion-tracking by using deep neural networks with multi-output.
Neural Comput. Appl.
Yangxu Wang, Hua Mao, Zhang Yi
2018 J jnl
Audio classification using attention-augmented convolutional neural network.
Knowl. Based Syst.
Yu Wu, Hua Mao, Zhang Yi
2018 J jnl
Symmetric low-rank preserving projections for subspace learning.
Neurocomputing
Jie Chen, Hua Mao, Haixian Zhang, Zhang Yi
2017 J jnl
Cell mitosis detection using deep neural networks.
Knowl. Based Syst.
Yao Zhou, Hua Mao, Zhang Yi
2017 J jnl
Cell tracking using deep neural networks with multi-task learning.
Image Vis. Comput.
Tao He, Hua Mao, Jixiang Guo, Zhang Yi
2017 J jnl
Explicit guiding auto-encoders for learning meaningful representation.
Neural Comput. Appl.
Yanan Sun, Hua Mao, Yongsheng Sang, Zhang Yi
2017 J jnl
Moving object recognition using multi-view three-dimensional convolutional neural networks.
Neural Comput. Appl.
Tao He, Hua Mao, Zhang Yi
2017 J jnl
Parameter as a Switch Between Dynamical States of a Network in Population Decoding.
IEEE Trans. Neural Networks Learn. Syst.
Jiali Yu, Hua Mao, Zhang Yi
2017 J jnl
Protein secondary structure prediction by using deep learning method.
Knowl. Based Syst.
Yangxu Wang, Hua Mao, Zhang Yi
2017 J jnl
Subspace clustering using a symmetric low-rank representation.
Knowl. Based Syst.
Jie Chen, Hua Mao, Yongsheng Sang, Zhang Yi
2016 J jnl
Approximating behavioral equivalence for scaling solutions of I-DIDs.
Knowl. Inf. Syst.
Yifeng Zeng, Prashant Doshi, Yingke Chen, Yinghui Pan, Hua Mao, Muthukumaran Chandrasekaran
2016 J jnl
Learning a good representation with unsymmetrical auto-encoder.
Neural Comput. Appl.
Yanan Sun, Hua Mao, Quan Guo, Zhang Yi
2016 J jnl
Learning deterministic probabilistic automata from a model checking perspective.
Mach. Learn.
Hua Mao, Yingke Chen, Manfred Jaeger, Thomas D. Nielsen, Kim G. Larsen, Brian Nielsen
2016 B conf
Manifold dimension reduction based clustering for multi-objective evolutionary algorithm.
CEC
Yanan Sun, Gary G. Yen, Hua Mao, Zhang Yi
2016 J jnl
Symmetric low-rank representation for subspace clustering.
Neurocomputing
Jie Chen, Haixian Zhang, Hua Mao, Yongsheng Sang, Zhang Yi
2014 — conf
Continuity Properties of Distances for Markov Processes.
QEST
Manfred Jaeger, Hua Mao, Kim Guldstrand Larsen, Radu Mardare
2014 — conf
Diversifying the Storytelling Using Bayesian Networks.
ADMI
Wenyun Wu, Biyang Ma, Shaoxin Zhang, Yifeng Zeng, Hua Mao
2014 — conf
Learning Agents' Relations in Interactive Multiagent Dynamic Influence Diagrams.
ADMI
Yinghui Pan, Yifeng Zeng, Hua Mao
2012 — conf
An Optimization Approach to Believable Behavior in Computer Games.
ADMI
Yifeng Zeng, Hua Mao, Fan Yang, Jian Luo
2012 A conf
Improved use of partial policies for identifying behavioral equivalence.
AAMAS
Yifeng Zeng, Hua Mao, Yinghui Pan, Jian Luo
2012 — conf
Learning Communication in Interactive Dynamic Influence Diagrams.
IAT
Yifeng Zeng, Hua Mao, Prashant Doshi, Yinghui Pan, Jian Luo
2012 — conf
Learning Markov Decision Processes for Model Checking
QFM
Hua Mao, Yingke Chen, Manfred Jaeger, Thomas D. Nielsen, Kim G. Larsen, Brian Nielsen
2012 — conf
Learning Markov Models for Stationary System Behaviors.
NASA Formal Methods
Yingke Chen, Hua Mao, Manfred Jaeger, Thomas Dyhre Nielsen, Kim Guldstrand Larsen, Brian Nielsen
2012 C conf
Learning and Model-Checking Networks of I/O Automata.
ACML
Hua Mao, Manfred Jaeger
2011 — conf
Dynamic Ordering-Based Search Algorithm for Markov Blanket Discovery.
PAKDD (2)
Yifeng Zeng, Xian He, Yanping Xiang, Hua Mao
2011 — conf
Learning Probabilistic Automata for Model Checking.
QEST
Hua Mao, Yingke Chen, Manfred Jaeger, Thomas D. Nielsen, Kim G. Larsen, Brian Nielsen
2011 A* conf
Utilizing Partial Policies for Identifying Equivalence of Behavioral Models.
AAAI
Yifeng Zeng, Prashant Doshi, Yinghui Pan, Hua Mao, Muthukumaran Chandrasekaran, Jian Luo