Bingxin Zhou
Cited by
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How framelets enhance graph neural networks
X Zheng, B Zhou, J Gao, YG Wang, P Lio, M Li, G Mont˙far
International Conference on Machine Learning, 2021
Decimated Framelet System on Graphs and Fast G-Framelet Transforms.
X Zheng, B Zhou, YG Wang, X Zhuang
J. Mach. Learn. Res. 23, 18:1-18:68, 2022
MathNet: Haar-Like Wavelet Multiresolution-Analysis for Graph Representation and Learning
X Zheng, B Zhou, M Li, YG Wang, J Gao
Knowledge-Based Systems, 2023
Graph denoising with framelet regularizer
B Zhou, R Li, X Zheng, YG Wang, J Gao
arXiv preprint arXiv:2111.03264, 2021
Manifold optimization-assisted gaussian variational approximation
B Zhou, J Gao, MN Tran, R Gerlach
Journal of Computational and Graphical Statistics 30 (4), 946-957, 2021
Well-conditioned Spectral Transforms for Dynamic Graph Representation
B Zhou, X Liu, Y Liu, Y Huang, P Lio, YG Wang
Learning on Graphs Conference, 2022
Graph neural network for local corruption recovery
B Zhou, Y Jiang, YG Wang, J Liang, J Gao, S Pan, X Zhang
The Web Conference, 2023
How Graph Neural Networks Enhance Convolutional Neural Networks Towards Mining the Topological Structures from Histology
Y Shen, B Zhou, X Xiong, R Gao, YG Wang
ICML Workshop on Computational Biology, 2022
Approximate Equivariance SO (3) Needlet Convolution
K Yi, J Chen, YG Wang, B Zhou, P Li˛, Y Fan, J Hamann
Proceedings of Topological, Algebraic, and Geometric Learning Workshops 2022á…, 2022
Grassmann Graph Embedding
B Zhou, X Zheng, YG Wang, M Li, J Gao
ICLR 2021 Workshop on Geometrical and Topological Representation Learning, 2021
On the trend-corrected variant of adaptive stochastic optimization methods
B Zhou, X Zheng, J Gao
2020 international joint conference on neural networks (IJCNN), 1-8, 2020
Lightweight Equivariant Graph Representation Learning for Protein Engineering
B Zhou, O Lv, K Yi, X Xiong, P Tan, L Hong, YG Wang
NeurIPS workshop on Machine Learning in Structural Biology, 2022
Robust Graph Representation Learning for Local Corruption Recovery
B Zhou, Y Jiang, YG Wang, J Liang, J Gao, S Pan, X Zhang
ICML Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), 2022
Accurate and Definite Mutational Effect Prediction with Lightweight Equivariant Graph Neural Networks
B Zhou, O Lv, K Yi, X Xiong, P Tan, L Hong, YG Wang
arXiv preprint arXiv:2304.08299, 2023
Graph Representation Learning for Interactive Biomolecule Systems
X Xiong, B Zhou, YG Wang
arXiv preprint arXiv:2304.02656, 2023
Framelet Message Passing
X Liu, B Zhou, C Zhang, YG Wang
arXiv preprint arXiv:2302.14806, 2023
Embedding graphs on Grassmann manifold
B Zhou, X Zheng, YG Wang, M Li, J Gao
Neural Networks 152, 322-331, 2022
How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images
Y Shen, B Zhou, X Xiong, R Gao, YG Wang
arXiv preprint arXiv:2206.07599, 2022
Framelet Message Passing: GNNs Propagation with Multiscale Multi-hop Representation and No Oversmoothing
X Liu, B Zhou, C Zhang, YG Wang
The 8th International Conference on Computational Harmonic Analysis (ICCHA2022), 2022
Geometric Signal Processing with Graph Neural Networks
B Zhou
The University of Sydney, 2022
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