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ORCIDYu Guang Wang 0001
Person information
- affiliation: Shanghai Jiao Tong University, School of Mathematical Sciences, Shanghai, China
- affiliation: University of New South Wales, School of Mathematics and Statistics, Sydney, Australia
Other persons with the same name
- Yuguang Wang (aka: Yu Guang Wang) — disambiguation page
- Yuguang Wang 0002 — Crrc Qingdao Sifang Co., Ltd., China
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Journal Articles
- 2023
[j16]Yuguang Wang, Robert S. Womersley
, Hau-Tieng Wu, Wei-Hsuan Yu:
Numerical computation of triangular complex spherical designs with small mesh ratio. J. Comput. Appl. Math. 421: 114796 (2023)- [j15]Xuebin Zheng, Bingxin Zhou, Ming Li, Yu Guang Wang, Junbin Gao:
MathNet: Haar-like wavelet multiresolution analysis for graph representation learning. Knowl. Based Syst. 273: 110609 (2023) - [j14]Hao Chen, Yu Guang Wang, Huan Xiong:
Lower and upper bounds for numbers of linear regions of graph convolutional networks. Neural Networks 168: 394-404 (2023) - [j13]Yixin Liu, Shirui Pan, Yu Guang Wang, Fei Xiong, Liang Wang, Qingfeng Chen, Vincent Cheng-Siong Lee:
Anomaly Detection in Dynamic Graphs via Transformer. IEEE Trans. Knowl. Data Eng. 35(12): 12081-12094 (2023) - 2022
- [j12]Guido Montúfar, Yu Guang Wang:
Distributed Learning via Filtered Hyperinterpolation on Manifolds. Found. Comput. Math. 22(4): 1219-1271 (2022) - [j11]Xuebin Zheng, Bingxin Zhou, Yu Guang Wang, Xiaosheng Zhuang:
Decimated Framelet System on Graphs and Fast G-Framelet Transforms. J. Mach. Learn. Res. 23: 18:1-18:68 (2022) - [j10]Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao:
Embedding graphs on Grassmann manifold. Neural Networks 152: 322-331 (2022) - 2021
- [j9]Shaobo Lin, Yuguang Wang, Ding-Xuan Zhou:
Distributed Filtered Hyperinterpolation for Noisy Data on the Sphere. SIAM J. Numer. Anal. 59(2): 634-659 (2021) - [j8]Quoc Thong Le Gia, Ming Li, Yu Guang Wang:
Algorithm 1018: FaVeST - Fast Vector Spherical Harmonic Transforms. ACM Trans. Math. Softw. 47(4): 39:1-39:24 (2021) - 2020
- [j7]Ming Li, Zheng Ma, Yu Guang Wang, Xiaosheng Zhuang:
Fast Haar Transforms for Graph Neural Networks. Neural Networks 128: 188-198 (2020) - 2018
- [j6]Johann S. Brauchart, Alexander B. Reznikov, Edward B. Saff, Ian H. Sloan, Yuguang Wang, Robert S. Womersley:
Random Point Sets on the Sphere - Hole Radii, Covering, and Separation. Exp. Math. 27(1): 62-81 (2018) - 2017
- [j5]Quoc Thong Le Gia, Ian H. Sloan, Yuguang Wang, Robert S. Womersley:
Needlet approximation for isotropic random fields on the sphere. J. Approx. Theory 216: 86-116 (2017) - 2016
- [j4]Feilong Cao, Dianhui Wang, Hou-Ying Zhu, Yuguang Wang:
An iterative learning algorithm for feedforward neural networks with random weights. Inf. Sci. 328: 546-557 (2016) - 2013
- [j3]Zhixiang Chen, Hou-Ying Zhu, Yuguang Wang:
A modified extreme learning machine with sigmoidal activation functions. Neural Comput. Appl. 22(3-4): 541-550 (2013) - 2011
- [j2]Yubo Yuan, Yuguang Wang, Feilong Cao:
Optimization approximation solution for regression problem based on extreme learning machine. Neurocomputing 74(16): 2475-2482 (2011) - [j1]Yuguang Wang, Feilong Cao, Yubo Yuan:
A study on effectiveness of extreme learning machine. Neurocomputing 74(16): 2483-2490 (2011)
Conference and Workshop Papers
- 2023
- [c16]Yiqing Shen, Bingxin Zhou, Xinye Xiong, Ruitian Gao, Yu Guang Wang:
How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images. BIBM 2023: 2227-2230 - [c15]Chenxin Xu, Robby T. Tan, Yuhong Tan, Siheng Chen, Yu Guang Wang, Xinchao Wang, Yanfeng Wang:
EqMotion: Equivariant Multi-Agent Motion Prediction with Invariant Interaction Reasoning. CVPR 2023: 1410-1420 - [c14]Xiongwen Ke, Houying Zhu, Kai Yi, Gaoning He, Ganghua Yang, Yu Guang Wang:
Adaptive Importance Sampling and Quasi-Monte Carlo Methods for 6G URLLC Systems. ICC 2023: 5272-5278 - [c13]Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin:
ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks. ICLR 2023 - [c12]Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Lió, Yuguang Wang:
Graph Denoising Diffusion for Inverse Protein Folding. NeurIPS 2023 - [c11]Bingxin Zhou, Yuanhong Jiang, Yuguang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang:
Robust Graph Representation Learning for Local Corruption Recovery. WWW 2023: 438-448 - 2022
- [c10]Pradeep Kr. Banerjee, Kedar Karhadkar, Yuguang Wang, Uri Alon, Guido Montúfar:
Oversquashing in GNNs through the lens of information contraction and graph expansion. Allerton 2022: 1-8 - [c9]Bingxin Zhou, Xinliang Liu, Yuehua Liu, Yunying Huang, Pietro Liò, Yuguang Wang:
Well-Conditioned Spectral Transforms for Dynamic Graph Representation. LoG 2022: 12 - [c8]Kai Yi, Jialin Chen, Yu Guang Wang, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann:
APPROXIMATE EQUIVARIANCE SO(3) NEEDLET CONVOLUTION. TAG-ML 2022: 189-198 - 2021
- [c7]Cristian Bodnar, Fabrizio Frasca, Yuguang Wang, Nina Otter, Guido F. Montúfar, Pietro Lió, Michael M. Bronstein:
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. ICML 2021: 1026-1037 - [c6]Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang, Pietro Lió, Ming Li, Guido Montúfar:
How Framelets Enhance Graph Neural Networks. ICML 2021: 12761-12771 - [c5]Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yuguang Wang, Pietro Liò, Guido F. Montúfar, Michael M. Bronstein:
Weisfeiler and Lehman Go Cellular: CW Networks. NeurIPS 2021: 2625-2640 - 2020
- [c4]Yuguang Wang, Ming Li, Zheng Ma, Guido Montúfar, Xiaosheng Zhuang, Yanan Fan:
Haar Graph Pooling. ICML 2020: 9952-9962 - [c3]Nicole Hallett, Kai Yi, Josef Dick, Christopher Hodge, Gerard Sutton, Yu Guang Wang, Jingjing You:
Deep Learning Based Unsupervised and Semi-supervised Classification for Keratoconus. IJCNN 2020: 1-7 - [c2]Kai Yi, Yi Guo, Yanan Fan, Jan Hamann, Yu Guang Wang:
Cosmo VAE: Variational Autoencoder for CMB Image Inpainting. IJCNN 2020: 1-7 - [c1]Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Liò:
Path Integral Based Convolution and Pooling for Graph Neural Networks. NeurIPS 2020
Informal and Other Publications
- 2024
- [i38]Wei Duan, Jie Lu, Yu Guang Wang, Junyu Xuan:
Layer-diverse Negative Sampling for Graph Neural Networks. CoRR abs/2403.11408 (2024) - 2023
- [i37]Xinliang Liu, Bingxin Zhou, Chutian Zhang, Yuguang Wang:
Framelet Message Passing. CoRR abs/2302.14806 (2023) - [i36]Chenxin Xu, Robby T. Tan, Yuhong Tan, Siheng Chen, Yu Guang Wang, Xinchao Wang, Yanfeng Wang:
EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning. CoRR abs/2303.10876 (2023) - [i35]Xinye Xiong, Bingxin Zhou, Yuguang Wang:
Graph Representation Learning for Interactive Biomolecule Systems. CoRR abs/2304.02656 (2023) - [i34]Bingxin Zhou, Outongyi Lv, Kai Yi, Xinye Xiong, Pan Tan, Liang Hong, Yu Guang Wang:
Accurate and Definite Mutational Effect Prediction with Lightweight Equivariant Graph Neural Networks. CoRR abs/2304.08299 (2023) - [i33]Yang Tan, Bingxin Zhou, Yuanhong Jiang, Yu Guang Wang, Liang Hong:
Multi-level Protein Representation Learning for Blind Mutational Effect Prediction. CoRR abs/2306.04899 (2023) - [i32]Kai Yi, Bingxin Zhou, Yiqing Shen, Pietro Liò, Yu Guang Wang:
Graph Denoising Diffusion for Inverse Protein Folding. CoRR abs/2306.16819 (2023) - [i31]Outongyi Lv, Bingxin Zhou, Yu Guang Wang:
LLQL: Logistic Likelihood Q-Learning for Reinforcement Learning. CoRR abs/2307.02345 (2023) - [i30]Jialin Chen, Yuelin Wang, Cristian Bodnar, Rex Ying, Pietro Lio, Yuguang Wang:
Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation. CoRR abs/2311.05767 (2023) - 2022
- [i29]Bingxin Zhou, Yuanhong Jiang, Yu Guang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang:
Graph Neural Network for Local Corruption Recovery. CoRR abs/2202.04936 (2022) - [i28]Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao:
Embedding Graphs on Grassmann Manifold. CoRR abs/2205.15068 (2022) - [i27]Hao Chen, Yu Guang Wang, Huan Xiong:
Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks. CoRR abs/2206.00228 (2022) - [i26]Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin:
ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle Phase Transition. CoRR abs/2206.05437 (2022) - [i25]Yiqing Shen, Bingxin Zhou, Xinye Xiong, Ruitian Gao, Yu Guang Wang:
How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images. CoRR abs/2206.07599 (2022) - [i24]Kai Yi, Jialin Chen, Yu Guang Wang, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann:
Approximate Equivariance SO(3) Needlet Convolution. CoRR abs/2206.10385 (2022) - [i23]Pradeep Kr. Banerjee, Kedar Karhadkar, Yu Guang Wang, Uri Alon, Guido Montúfar:
Oversquashing in GNNs through the lens of information contraction and graph expansion. CoRR abs/2208.03471 (2022) - 2021
- [i22]Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Liò, Ming Li, Guido Montúfar:
How Framelets Enhance Graph Neural Networks. CoRR abs/2102.06986 (2021) - [i21]Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montúfar, Pietro Liò, Michael M. Bronstein:
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. CoRR abs/2103.03212 (2021) - [i20]Yixin Liu, Shirui Pan, Yu Guang Wang, Fei Xiong, Liang Wang, Vincent C. S. Lee:
Anomaly Detection in Dynamic Graphs via Transformer. CoRR abs/2106.09876 (2021) - [i19]Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yu Guang Wang, Pietro Liò, Guido Montúfar, Michael M. Bronstein:
Weisfeiler and Lehman Go Cellular: CW Networks. CoRR abs/2106.12575 (2021) - [i18]Bingxin Zhou, Ruikun Li, Xuebin Zheng, Yu Guang Wang, Junbin Gao:
Graph Denoising with Framelet Regularizer. CoRR abs/2111.03264 (2021) - [i17]Bingxin Zhou, Xinliang Liu, Yuehua Liu, Yunying Huang, Pietro Liò, Yuguang Wang:
Spectral Transform Forms Scalable Transformer. CoRR abs/2111.07602 (2021) - 2020
- [i16]Kai Yi, Yi Guo, Yanan Fan, Jan Hamann, Yuguang Wang:
CosmoVAE: Variational Autoencoder for CMB Image Inpainting. CoRR abs/2001.11651 (2020) - [i15]Nicole Hallett, Kai Yi, Josef Dick, Christopher Hodge, Gerard Sutton, Yu Guang Wang, Jingjing You:
Deep Learning Based Unsupervised and Semi-supervised Classification for Keratoconus. CoRR abs/2001.11653 (2020) - [i14]Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Lió:
Path Integral Based Convolution and Pooling for Graph Neural Networks. CoRR abs/2006.16811 (2020) - [i13]Guido Montúfar, Yu Guang Wang:
Distributed Learning via Filtered Hyperinterpolation on Manifolds. CoRR abs/2007.09392 (2020) - [i12]Xuebin Zheng, Bingxin Zhou, Ming Li, Yu Guang Wang, Junbin Gao:
Graph Neural Networks with Haar Transform-Based Convolution and Pooling: A Complete Guide. CoRR abs/2007.11202 (2020) - [i11]Sho Sonoda, Ming Li, Feilong Cao, Changqin Huang, Yu Guang Wang:
On the Approximation Lower Bound for Neural Nets with Random Weights. CoRR abs/2008.08427 (2020) - [i10]Guido Montúfar, Nina Otter, Yuguang Wang:
Can neural networks learn persistent homology features? CoRR abs/2011.14688 (2020) - [i9]Xuebin Zheng, Bingxin Zhou, Yu Guang Wang, Xiaosheng Zhuang:
Decimated Framelet System on Graphs and Fast G-Framelet Transforms. CoRR abs/2012.06922 (2020) - 2019
- [i8]Zheng Ma, Ming Li, Yu Guang Wang:
PAN: Path Integral Based Convolution for Deep Graph Neural Networks. CoRR abs/1904.10996 (2019) - [i7]Ming Li, Zheng Ma, Yu Guang Wang, Xiaosheng Zhuang:
Fast Haar Transforms for Graph Neural Networks. CoRR abs/1907.04786 (2019) - [i6]Ming Li, Philip Broadbridge, Andriy Olenko, Yu Guang Wang:
Fast Tensor Needlet Transforms for Tangent Vector Fields on the Sphere. CoRR abs/1907.13339 (2019) - [i5]Matt Sourisseau, Yu Guang Wang, Hau-Tieng Wu, Wei-Hsuan Yu:
Optimization-based quasi-uniform spherical t-design and generalized multitaper for complex physiological time series. CoRR abs/1907.13493 (2019) - [i4]Quoc Thong Le Gia, Ming Li, Yu Guang Wang:
FaVeST: Fast Vector Spherical Harmonic Transforms. CoRR abs/1908.00041 (2019) - [i3]Yu Guang Wang, Ming Li, Zheng Ma, Guido Montúfar, Xiaosheng Zhuang, Yanan Fan:
HaarPooling: Graph Pooling with Compressive Haar Basis. CoRR abs/1909.11580 (2019) - [i2]Shao-Bo Lin, Yu Guang Wang, Ding-Xuan Zhou:
Distributed filtered hyperinterpolation for noisy data on the sphere. CoRR abs/1910.02434 (2019) - 2014
- [i1]Yuguang Wang, Feilong Cao, Yubo Yuan:
A study on effectiveness of extreme learning machine. CoRR abs/1409.3924 (2014)
Coauthor Index
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