| A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network DQ Nguyen, TD Nguyen, DQ Nguyen, D Phung arXiv preprint arXiv:1712.02121, 2017 | 1066 | 2017 |
| Dual Discriminator Generative Adversarial Nets TD Nguyen, T Le, H Vu, D Phung arXiv preprint arXiv:1709.03831, 2017 | 419 | 2017 |
| MGAN: Training Generative Adversarial Nets with Multiple Generators Q Hoang, TD Nguyen, T Le, D Phung | 371* | 2018 |
| A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization DQ Nguyen, T Vu, TD Nguyen, DQ Nguyen, D Phung arXiv preprint arXiv:1808.04122, 2018 | 349 | 2018 |
| A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization DQ Nguyen, T Vu, TD Nguyen, DQ Nguyen, D Phung arXiv preprint arXiv:1808.04122, 2018 | 349 | 2018 |
| Animal recognition and identification with deep convolutional neural networks for automated wildlife monitoring H Nguyen, SJ Maclagan, TD Nguyen, T Nguyen, P Flemons, K Andrews, ... 2017 IEEE International Conference on Data Science and Advanced Analytics …, 2017 | 264 | 2017 |
| Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM) T Tran, TD Nguyen, D Phung, S Venkatesh Journal of biomedical informatics 54, 96-105, 2015 | 211 | 2015 |
| Robust anomaly detection in videos using multilevel representations H Vu, TD Nguyen, T Le, W Luo, D Phung Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5216-5223, 2019 | 113 | 2019 |
| Universal graph transformer self-attention networks DQ Nguyen, TD Nguyen, D Phung Companion Proceedings of the Web Conference 2022, 193-196, 2022 | 85 | 2022 |
| Large-scale online kernel learning with random feature reparameterization TD Nguyen, T Le, H Bui, D Phung Proceedings of the 26th International Joint Conference on Artificial …, 2017 | 66 | 2017 |
| Learning graph representation via frequent subgraphs D Nguyen, W Luo, TD Nguyen, S Venkatesh, D Phung Proceedings of the 2018 SIAM International Conference on Data Mining, 306-314, 2018 | 55 | 2018 |
| A convolutional neural network-based model for knowledge base completion and its application to search personalization DQ Nguyen, DQ Nguyen, TD Nguyen, D Phung Semantic Web 10 (5), 947-960, 2019 | 51 | 2019 |
| Learning parts-based representations with nonnegative restricted boltzmann machine TD Nguyen, T Tran, D Phung, S Venkatesh Asian Conference on Machine Learning, 133-148, 2013 | 44 | 2013 |
| Sqn2vec: Learning sequence representation via sequential patterns with a gap constraint D Nguyen, W Luo, TD Nguyen, S Venkatesh, D Phung Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019 | 40 | 2019 |
| Energy-Based Localized Anomaly Detection in Video Surveillance H Vu, TD Nguyen, A Travers, S Venkatesh, D Phung Pacific-Asia Conference on Knowledge Discovery and Data Mining, 641-653, 2017 | 40 | 2017 |
| Tensor-variate restricted Boltzmann machines TD Nguyen, T Tran, D Phung, S Venkatesh Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015 | 39 | 2015 |
| Quatre: Relation-aware quaternions for knowledge graph embeddings DQ Nguyen, T Vu, TD Nguyen, D Phung Companion Proceedings of the Web Conference 2022, 189-192, 2022 | 38 | 2022 |
| Quaternion graph neural networks TD Nguyen, D Phung Asian Conference on Machine Learning, 236-251, 2021 | 38 | 2021 |
| Energy-based Models for Video Anomaly Detection H Vu, D Phung, TD Nguyen, A Trevors, S Venkatesh arXiv preprint arXiv:1708.05211, 2017 | 31 | 2017 |
| Latent Patient Profile Modelling and Applications with Mixed-Variate Restricted Boltzmann Machine TD Nguyen, T Tran, D Phung, S Venkatesh Advances in Knowledge Discovery and Data Mining 7818, 123-135, 2013 | 30 | 2013 |
Dinh PhungProfessor, Monash UniversityBestätigte E-Mail-Adresse bei monash.edu