| DeepCU: Integrating both Common and Unique Latent Information for Multimodal Sentiment Analysis S Verma, C Wang, L Zhu, W Liu IJCAI 2019, 2019 | 37 | 2019 |
| Variational Co-embedding Learning for Attributed Network Clustering S Yang, S Verma, B Cai, J Jiang, K Yu, F Chen, S Yu arXiv preprint arXiv:2104.07295, 2021 | 29 | 2021 |
| Imitation Learning: Progress, Taxonomies and Challenges B Zheng, S Verma, J Zhou, IW Tsang, F Chen IEEE Transactions on Neural Networks and Learning Systems, 1-16, 2022 | 19 | 2022 |
| Deep-HOSeq: Deep Higher Order Sequence Fusion for Multimodal Sentiment Analysis S Verma, J Wang, Z Ge, R Shen, F Jin, Y Wang, F Chen, W Liu ICDM: International Conference on Data Mining, 2020, 561--570, 2020 | 15 | 2020 |
| Learning discriminability-preserving histogram representation from unordered features for multibiometric feature-fused-template protection MH Lim, S Verma, G Mai, PC Yuen Pattern Recognition 60, 706-719, 2016 | 13 | 2016 |
| A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics Y Li, J Zhou, S Verma, F Chen arXiv preprint arXiv:2207.12599, 2022 | 6 | 2022 |
| Hybrid networks: Improving deep learning networks via integrating two views of images S Verma, W Liu, C Wang, L Zhu Neural Information Processing: 25th International Conference, ICONIP 2018 …, 2018 | 6 | 2018 |
| Extracting Highly Effective Features for Supervised Learning via Simultaneous Tensor Factorization. S Verma, W Liu, C Wang, L Zhu AAAI, 4995-4996, 2017 | 6 | 2017 |
| Understanding Relations Between Perception of Fairness and Trust in Algorithmic Decision Making J Zhou, S Verma, M Mittal, F Chen 2021 8th International Conference on Behavioral and Social Computing (BESC), 1-5, 2021 | 4 | 2021 |
| Detection of anomalous traffic patterns and insight analysis from bus trajectory data X Zhang, X Zhang, S Verma, Y Liu, M Blumenstein, J Li PRICAI 2019: Trends in Artificial Intelligence: 16th Pacific Rim …, 2019 | 4 | 2019 |
| Attn-HybridNet: improving discriminability of hybrid features with attention fusion S Verma, C Wang, L Zhu, W Liu IEEE Transactions on Cybernetics 52 (7), 6567-6578, 2021 | 2 | 2021 |
| A Compliance Checking Framework for DNN Models S Verma, C Wang, L Zhu, W Liu IJCAI 2019, 2019 | 2 | 2019 |
| Are Graph Neural Network Explainers Robust to Graph Noises? Y Li, S Verma, S Yang, J Zhou, F Chen AI 2022: Advances in Artificial Intelligence: 35th Australasian Joint …, 2022 | 1 | 2022 |
| Interpretable Binaural Ratio for Visually Guided Binaural Audio Generation T Zheng, S Verma, W Liu 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 1 | 2022 |
| Fairness and Cost Constrained Privacy-Aware Record Linkage N Wu, D Vatsalan, S Verma, MA Kaafar IEEE Transactions on Information Forensics and Security 17, 2644-2656, 2022 | 1 | 2022 |
| A Data Driven Approach for Leak Detection with Smart Sensors B Liang, S Verma, J Xu, S Liang, Z Li, Y Wang, F Chen 2020 16th International Conference on Control, Automation, Robotics and …, 2020 | 1 | 2020 |
| Enhancing Sydney Water’s Leak Prevention Through Acoustic Monitoring R Nikoloska, L Bykerk, D Vitanage, JV Miro, F Chen, Y Wang, B Liang, ... Water e-Journal, 2020 | 1 | 2020 |
| DDoD: Dual Denial of Decision Attacks on Human-AI Teams B Tag, N van Berkel, S Verma, BZH Zhao, S Berkovsky, D Kaafar, ... IEEE Pervasive Computing, 2023 | | 2023 |
| Imitation Learning: Progress, Taxonomies and Opportunities B Zheng, S Verma, J Zhou, I Tsang, F Chen arXiv preprint arXiv:2106.12177, 2021 | | 2021 |
| Common and Unique Feature Learning for Data Fusion S Verma | | 2020 |
Wei LiuUniversity of Technology SydneyVerified email at uts.edu.au
