Yu Guang Wang

Orcid: 0000-0002-7450-0273

Affiliations:

Shanghai Jiao Tong University, School of Mathematical Sciences, Shanghai, China
University of New South Wales, School of Mathematics and Statistics, Sydney, Australia

According to our database¹, Yu Guang Wang authored at least 53 papers between 2011 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Layer-diverse Negative Sampling for Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Anomaly Detection in Dynamic Graphs via Transformer.

[BibT_eX]

[DOI]

Vincent Cheng-Siong Lee

IEEE Trans. Knowl. Data Eng., December, 2023

Lower and upper bounds for numbers of linear regions of graph convolutional networks.

[BibT_eX]

[DOI]

Hao Chen

Yu Guang Wang

Huan Xiong

Neural Networks, November, 2023

MathNet: Haar-like wavelet multiresolution analysis for graph representation learning.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2023

Numerical computation of triangular complex spherical designs with small mesh ratio.

[BibT_eX]

[DOI]

J. Comput. Appl. Math., 2023

Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation.

[BibT_eX]

[DOI]

CoRR, 2023

LLQL: Logistic Likelihood Q-Learning for Reinforcement Learning.

[BibT_eX]

[DOI]

Outongyi Lv

Bingxin Zhou

Yu Guang Wang

CoRR, 2023

Multi-level Protein Representation Learning for Blind Mutational Effect Prediction.

[BibT_eX]

[DOI]

CoRR, 2023

Accurate and Definite Mutational Effect Prediction with Lightweight Equivariant Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

Graph Representation Learning for Interactive Biomolecule Systems.

[BibT_eX]

[DOI]

Xinye Xiong

Bingxin Zhou

Yuguang Wang

CoRR, 2023

Framelet Message Passing.

[BibT_eX]

[DOI]

CoRR, 2023

Robust Graph Representation Learning for Local Corruption Recovery.

[BibT_eX]

[DOI]

Proceedings of the ACM Web Conference 2023, 2023

Graph Denoising Diffusion for Inverse Protein Folding.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Adaptive Importance Sampling and Quasi-Monte Carlo Methods for 6G URLLC Systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

EqMotion: Equivariant Multi-Agent Motion Prediction with Invariant Interaction Reasoning.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022

Embedding graphs on Grassmann manifold.

[BibT_eX]

[DOI]

Neural Networks, 2022

Decimated Framelet System on Graphs and Fast G-Framelet Transforms.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Distributed Learning via Filtered Hyperinterpolation on Manifolds.

[BibT_eX]

[DOI]

Guido Montúfar

Yu Guang Wang

Found. Comput. Math., 2022

ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle Phase Transition.

[BibT_eX]

[DOI]

CoRR, 2022

Graph Neural Network for Local Corruption Recovery.

[BibT_eX]

[DOI]

CoRR, 2022

APPROXIMATE EQUIVARIANCE SO(3) NEEDLET CONVOLUTION.

[BibT_eX]

[DOI]

Proceedings of the Topological, 2022

Well-Conditioned Spectral Transforms for Dynamic Graph Representation.

[BibT_eX]

[DOI]

Proceedings of the Learning on Graphs Conference, 2022

Oversquashing in GNNs through the lens of information contraction and graph expansion.

[BibT_eX]

[DOI]

Proceedings of the 58th Annual Allerton Conference on Communication, 2022

2021

Algorithm 1018: FaVeST - Fast Vector Spherical Harmonic Transforms.

[BibT_eX]

[DOI]

Quoc Thong Le Gia

Ming Li

Yu Guang Wang

ACM Trans. Math. Softw., 2021

Distributed Filtered Hyperinterpolation for Noisy Data on the Sphere.

[BibT_eX]

[DOI]

Shaobo Lin

Yuguang Wang

Ding-Xuan Zhou

SIAM J. Numer. Anal., 2021

Spectral Transform Forms Scalable Transformer.

[BibT_eX]

[DOI]

CoRR, 2021

Graph Denoising with Framelet Regularizer.

[BibT_eX]

[DOI]

CoRR, 2021

Anomaly Detection in Dynamic Graphs via Transformer.

[BibT_eX]

[DOI]

CoRR, 2021

Weisfeiler and Lehman Go Cellular: CW Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How Framelets Enhance Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Fast Haar Transforms for Graph Neural Networks.

[BibT_eX]

[DOI]

Neural Networks, 2020

Can neural networks learn persistent homology features?

[BibT_eX]

[DOI]

Guido Montúfar

Nina Otter

Yuguang Wang

CoRR, 2020

On the Approximation Lower Bound for Neural Nets with Random Weights.

[BibT_eX]

[DOI]

CoRR, 2020

Graph Neural Networks with Haar Transform-Based Convolution and Pooling: A Complete Guide.

[BibT_eX]

[DOI]

CoRR, 2020

CosmoVAE: Variational Autoencoder for CMB Image Inpainting.

[BibT_eX]

[DOI]

CoRR, 2020

Path Integral Based Convolution and Pooling for Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cosmo VAE: Variational Autoencoder for CMB Image Inpainting.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Deep Learning Based Unsupervised and Semi-supervised Classification for Keratoconus.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Haar Graph Pooling.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

HaarPooling: Graph Pooling with Compressive Haar Basis.

[BibT_eX]

[DOI]

CoRR, 2019

FaVeST: Fast Vector Spherical Harmonic Transforms.

[BibT_eX]

[DOI]

Quoc Thong Le Gia

Ming Li

Yu Guang Wang

CoRR, 2019

Optimization-based quasi-uniform spherical t-design and generalized multitaper for complex physiological time series.

[BibT_eX]

[DOI]

CoRR, 2019

Fast Tensor Needlet Transforms for Tangent Vector Fields on the Sphere.

[BibT_eX]

[DOI]

CoRR, 2019

PAN: Path Integral Based Convolution for Deep Graph Neural Networks.

[BibT_eX]

[DOI]

Zheng Ma

Ming Li

Yu Guang Wang

CoRR, 2019

2018

Random Point Sets on the Sphere - Hole Radii, Covering, and Separation.

[BibT_eX]

[DOI]

Johann S. Brauchart

Alexander B. Reznikov

Exp. Math., 2018

2017

Needlet approximation for isotropic random fields on the sphere.

[BibT_eX]

[DOI]

J. Approx. Theory, 2017

2016

An iterative learning algorithm for feedforward neural networks with random weights.

[BibT_eX]

[DOI]

Inf. Sci., 2016

2013

A modified extreme learning machine with sigmoidal activation functions.

[BibT_eX]

[DOI]

Zhixiang Chen

Hou-Ying Zhu

Yuguang Wang

Neural Comput. Appl., 2013

2011

Optimization approximation solution for regression problem based on extreme learning machine.

[BibT_eX]

[DOI]

Yubo Yuan

Yuguang Wang

Feilong Cao

Neurocomputing, 2011

A study on effectiveness of extreme learning machine.

[BibT_eX]

[DOI]

Yuguang Wang

Feilong Cao

Yubo Yuan

Neurocomputing, 2011

Yu Guang Wang

Timeline

Legend:

Links

Online presence:

On csauthors.net:

Bibliography

Loading...