| Augmentation-free graph contrastive learning with performance guarantee H Wang, J Zhang, Q Zhu, W Huang arXiv preprint arXiv:2204.04874, 2022 | 26 | 2022 |
| Critical percolation clusters in seven dimensions and on a complete graph W Huang, P Hou, J Wang, RM Ziff, Y Deng Physical Review E 97 (2), 022107, 2018 | 21 | 2018 |
| On the neural tangent kernel of deep networks with orthogonal initialization W Huang, W Du, RY Da Xu IJCAI 2021, 2020 | 20 | 2020 |
| Auto-scaling Vision Transformers without Training W Chen, W Huang, X Du, X Song, Z Wang, D Zhou ICLR 2022, 2022 | 15 | 2022 |
| Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective W Huang, Y Li, W Du, RY Da Xu, J Yin, L Chen, M Zhang ICLR 2022, 2021 | 15* | 2021 |
| Adaptive multi-GPU exchange Monte Carlo for the 3D random field Ising model CA Navarro, W Huang, Y Deng Computer Physics Communications 205, 48-60, 2016 | 15 | 2016 |
| Deep Active Learning by Leveraging Training Dynamics H Wang, W Huang, A Margenot, H Tong, J He NeurIPS 2022, 2021 | 9 | 2021 |
| On the Equivalence between Neural Network and Support Vector Machine Y Chen, W Huang, LM Nguyen, TW Weng NeurIPS 2021, Thirty-Fifth Conference on Neural Information Processing Systems, 2021 | 9 | 2021 |
| Differentiable Architecture Search Meets Network Pruning at Initialization: A More Reliable, Efficient, and Flexible Framework M Zhang, S Su, S Pan, X Chang, W Huang, B Yang, G Haffari arXiv preprint arXiv:2106.11542, 2021 | 5* | 2021 |
| Mean field theory for deep dropout networks: digging up gradient backpropagation deeply W Huang, RYD Xu, W Du, Y Zeng, Y Zhao ECAI 2020, the 24th European Conference on Artificial Intelligence, 2020 | 5 | 2020 |
| Analyzing Deep PAC-Bayesian Learning with Neural Tangent Kernel: Convergence, Analytic Generalization Bound, and Efficient Hyperparameter Selection W Huang, C Liu, Y Chen, RY Da Xu, M Zhang, TW Weng Transactions on Machine Learning Research, 2023 | 4* | 2023 |
| Towards Understanding Feature Learning in Out-of-Distribution Generalization Y Chen, W Huang, K Zhou, Y Bian, B Han, J Cheng arXiv preprint arXiv:2304.11327, 2023 | 4 | 2023 |
| Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis W Chen, W Huang, X Gong, B Hanin, Z Wang NeurIPS 2022, 2022 | 4 | 2022 |
| Pruning graph neural networks by evaluating edge properties L Wang, W Huang, M Zhang, S Pan, X Chang, SW Su Knowledge-Based Systems 256, 109847, 2022 | 3 | 2022 |
| Gaussian process latent variable model factorization for context-aware recommender systems W Huang, RY Da Xu Pattern Recognition Letters 151, 281-287, 2021 | 3 | 2021 |
| Implicit bias of deep linear networks in the large learning rate phase W Huang, W Du, RY Da Xu, C Liu arXiv preprint arXiv:2011.12547, 2020 | 3* | 2020 |
| Can Single-Pass Contrastive Learning Work for Both Homophilic and Heterophilic Graph? H Wang, J Zhang, Q Zhu, W Huang arXiv preprint arXiv:2211.10890, 2022 | 1 | 2022 |
| Weighted Mutual Learning with Diversity-Driven Model Compression M Zhang, L Wang, DGC Campos, W Huang, C Guo, B Yang Advances in Neural Information Processing Systems, 2022 | 1 | 2022 |
| “No Free Lunch” in Neural Architectures? A Joint Analysis of Expressivity, Convergence, and Generalization W Chen, W Huang, Z Wang AutoML Conference 2023, 2023 | | 2023 |
| Causal Neural Graph Collaborative Filtering X Wang, Q Li, D Yu, W Huang, G Xu arXiv preprint arXiv:2307.04384, 2023 | | 2023 |
Prof Richard Yi Da XuHong Kong Baptist UniversityVerified email at hkbu.edu.hk
