Yu Guang Wang

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 42

Top Topics

Top Venues

Neural Networks

Publications

Yiqing Shen, Outongyi Lv, Houying Zhu, Yu Guang Wang
ProteinEngine: Empower LLM with Domain Knowledge for Protein Engineering. AIME (1) (2024)
Wei Duan, Jie Lu, Yu Guang Wang, Junyu Xuan
Layer-diverse Negative Sampling for Graph Neural Networks. Trans. Mach. Learn. Res. 2024 (2024)
Ming Li, Alessio Micheli, Yu Guang Wang, Shirui Pan, Pietro Lió, Giorgio Stefano Gnecco, Marcello Sanguineti
Guest Editorial: Deep Neural Networks for Graphs: Theory, Models, Algorithms, and Applications. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Wei Duan, Jie Lu, Yu Guang Wang, Junyu Xuan
Layer-diverse Negative Sampling for Graph Neural Networks. CoRR (2024)
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 (2023)
Hao Chen, Yu Guang Wang, Huan Xiong
Lower and upper bounds for numbers of linear regions of graph convolutional networks. Neural Networks 168 (2023)
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) (2023)
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)
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)
Kai Yi, Jialin Chen, Yu Guang Wang, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann
Approximate Equivariance SO(3) Needlet Convolution. CoRR (2022)
Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao
Embedding Graphs on Grassmann Manifold. CoRR (2022)
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 (2022)
Hao Chen, Yu Guang Wang, Huan Xiong
Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks. CoRR (2022)
Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao
Embedding graphs on Grassmann manifold. Neural Networks 152 (2022)
Bingxin Zhou, Yuanhong Jiang, Yu Guang Wang, Jingwei Liang, Junbin Gao, Shirui Pan, Xiaoqun Zhang
Graph Neural Network for Local Corruption Recovery. CoRR (2022)
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 (2022)
Kai Yi, Jialin Chen, Yu Guang Wang, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann
APPROXIMATE EQUIVARIANCE SO(3) NEEDLET CONVOLUTION. TAG-ML (2022)
Xuebin Zheng, Bingxin Zhou, Yu Guang Wang, Xiaosheng Zhuang
Decimated Framelet System on Graphs and Fast G-Framelet Transforms. J. Mach. Learn. Res. 23 (2022)
Guido Montúfar, Yu Guang Wang
Distributed Learning via Filtered Hyperinterpolation on Manifolds. Found. Comput. Math. 22 (4) (2022)
Quoc Thong Le Gia, Ming Li, Yu Guang Wang
Algorithm 1018: FaVeST - Fast Vector Spherical Harmonic Transforms. ACM Trans. Math. Softw. 47 (4) (2021)
Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yu Guang Wang, Pietro Liò, Guido Montúfar, Michael M. Bronstein
Weisfeiler and Lehman Go Cellular: CW Networks. CoRR (2021)
Yixin Liu, Shirui Pan, Yu Guang Wang, Fei Xiong, Liang Wang, Vincent C. S. Lee
Anomaly Detection in Dynamic Graphs via Transformer. CoRR (2021)
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 (2021)
Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Liò, Ming Li, Guido Montúfar
How Framelets Enhance Graph Neural Networks. CoRR (2021)
Bingxin Zhou, Ruikun Li, Xuebin Zheng, Yu Guang Wang, Junbin Gao
Graph Denoising with Framelet Regularizer. CoRR (2021)
Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Liò
Path Integral Based Convolution and Pooling for Graph Neural Networks. NeurIPS (2020)
Sho Sonoda, Ming Li, Feilong Cao, Changqin Huang, Yu Guang Wang
On the Approximation Lower Bound for Neural Nets with Random Weights. CoRR (2020)
Ming Li, Zheng Ma, Yu Guang Wang, Xiaosheng Zhuang
Fast Haar Transforms for Graph Neural Networks. Neural Networks 128 (2020)
Xuebin Zheng, Bingxin Zhou, Yu Guang Wang, Xiaosheng Zhuang
Decimated Framelet System on Graphs and Fast G-Framelet Transforms. CoRR (2020)
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)
Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Lió
Path Integral Based Convolution and Pooling for Graph Neural Networks. CoRR (2020)
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 (2020)
Guido Montúfar, Yu Guang Wang
Distributed Learning via Filtered Hyperinterpolation on Manifolds. CoRR (2020)
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 (2020)
Kai Yi, Yi Guo, Yanan Fan, Jan Hamann, Yu Guang Wang
Cosmo VAE: Variational Autoencoder for CMB Image Inpainting. IJCNN (2020)
Ming Li, Zheng Ma, Yu Guang Wang, Xiaosheng Zhuang
Fast Haar Transforms for Graph Neural Networks. CoRR (2019)
Yu Guang Wang, Ming Li, Zheng Ma, Guido Montúfar, Xiaosheng Zhuang, Yanan Fan
HaarPooling: Graph Pooling with Compressive Haar Basis. CoRR (2019)
Shao-Bo Lin, Yu Guang Wang, Ding-Xuan Zhou
Distributed filtered hyperinterpolation for noisy data on the sphere. CoRR (2019)
Quoc Thong Le Gia, Ming Li, Yu Guang Wang
FaVeST: Fast Vector Spherical Harmonic Transforms. CoRR (2019)
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 (2019)
Zheng Ma, Ming Li, Yu Guang Wang
PAN: Path Integral Based Convolution for Deep Graph Neural Networks. CoRR (2019)
Ming Li, Philip Broadbridge, Andriy Olenko, Yu Guang Wang
Fast Tensor Needlet Transforms for Tangent Vector Fields on the Sphere. CoRR (2019)