| On Riemannian optimization over positive definite matrices with the Bures-Wasserstein geometry A Han, B Mishra, PK Jawanpuria, J Gao Advances in Neural Information Processing Systems 34, 8940-8953, 2021 | 19 | 2021 |
| Improved variance reduction methods for Riemannian non-convex optimization A Han, J Gao IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 7610 …, 2021 | 13* | 2021 |
| Riemannian Hamiltonian methods for min-max optimization on manifolds A Han, B Mishra, P Jawanpuria, P Kumar, J Gao SIAM Journal on Optimization 33 (3), 1797-1827, 2023 | 8 | 2023 |
| Riemannian stochastic recursive momentum method for non-convex optimization A Han, J Gao arXiv preprint arXiv:2008.04555, 2020 | 7 | 2020 |
| A Simple Yet Effective Framelet-Based Graph Neural Network for Directed Graphs C Zou, A Han, L Lin, M Li, J Gao IEEE Transactions on Artificial Intelligence, 2023 | 6* | 2023 |
| Generalized energy and gradient flow via graph framelets A Han, D Shi, Z Shao, J Gao arXiv preprint arXiv:2210.04124, 2022 | 6 | 2022 |
| Differentially private Riemannian optimization A Han, B Mishra, P Jawanpuria, J Gao arXiv preprint arXiv:2205.09494, 2022 | 4 | 2022 |
| Escape saddle points faster on manifolds via perturbed riemannian stochastic recursive gradient A Han, J Gao arXiv preprint arXiv:2010.12191, 2020 | 4 | 2020 |
| Learning with symmetric positive definite matrices via generalized Bures-Wasserstein geometry A Han, B Mishra, P Jawanpuria, J Gao International Conference on Geometric Science of Information, 405-415, 2023 | 3* | 2023 |
| Generalized Laplacian Regularized Framelet GCNs Z Shao, A Han, D Shi, A Vasnev, J Gao arXiv preprint arXiv:2210.15092, 2022 | 3 | 2022 |
| Riemannian block SPD coupling manifold and its application to optimal transport A Han, B Mishra, P Jawanpuria, J Gao Machine Learning, 1-28, 2022 | 3 | 2022 |
| Riemannian accelerated gradient methods via extrapolation A Han, B Mishra, P Jawanpuria, J Gao International Conference on Artificial Intelligence and Statistics, 1554-1585, 2023 | 2 | 2023 |
| Rieoptax: Riemannian Optimization in JAX S Utpala, A Han, P Jawanpuria, B Mishra arXiv preprint arXiv:2210.04840, 2022 | 2 | 2022 |
| Fixed Point Laplacian Mapping: A Geometrically Correct Manifold Learning Algorithm D Shi, A Han, Y Guo, J Gao 2023 International Joint Conference on Neural Networks (IJCNN), 1-9, 2023 | 1* | 2023 |
| Robust Denoising in Graph Neural Networks S Zhang, A Han, J Gao 2022 IEEE Symposium Series on Computational Intelligence (SSCI), 1088-1095, 2022 | 1 | 2022 |
| Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond Z Shao, D Shi, A Han, Y Guo, Q Zhao, J Gao arXiv preprint arXiv:2309.02769, 2023 | | 2023 |
| Nonconvex-nonconcave min-max optimization on Riemannian manifolds A Han, B Mishra, P Jawanpuria, J Gao Transactions on Machine Learning Research, 2023 | | 2023 |
| Optimization and Learning over Riemannian Manifolds A Han | | 2023 |
| Improved Differentially Private Riemannian Optimization: Fast Sampling and Variance Reduction S Utpala, A Han, P Jawanpuria, B Mishra Transactions on Machine Learning Research, 2022 | | 2022 |
| On the Expressive Equivalence Between Graph Convolution and Attention Models D Shi, A Han, J Gao, Y Guo | | 2022 |
Professor Junbin GaoDiscipline of Business Analytics in Business School, The University of SydneyVerified email at sydney.edu.au
