Dr Yu Guang Wang

Dr Yu Guang Wang

Adjunct Associate Professor
Science
School of Mathematics & Statistics

I am an adjunct associate lecturer at UNSW Sydney. I am also a scientist at Max Planck Institute for Mathematics in Sciences, in Mathematics Machine Learning group, hosted by Prof Guido Montúfar. My research interests lie in computational mathematics, statistics, machine learning, and data science. In particular, I am working on deep learning, graph neural networks, applied harmonic analysis, Bayesian inference, information geometry, random fields, numerical analysis, and applications to healthcare, biomedical technology and cosmology. I obtained my PhD in applied mathematics from University of New South Wales under supervision of Prof Ian Sloan and Rob Womersley. I have been a semester-long visitor of IPAM, UCLA (2019) and ICERM, Brown University (2018).

Phone
9385 7076/4239
Location
School of Mathematics and Statistics UNSW Sydney NSW 2052 The Red Centre Room 2075
  • Book Chapters | 2022
    Hallett N; Hodge C; You JJ; Wang YG; Sutton G, 2022, 'Artificial Intelligence in the Diagnosis and Management of Keratoconus', in Keratoconus: Diagnosis and Treatment, pp. 275 - 289, http://dx.doi.org/10.1007/978-981-19-4262-4_22
    Book Chapters | 2018
    2018, 'Analysis of framelet transforms on a simplex', in , http://dx.doi.org/10.1007/978-3-319-72456-0_54
  • Journal articles | 2024
    Chen H; Wang YG; Xiong H, 2024, 'Corrigendum to “Lower and upper bounds for numbers of linear regions of graph convolutional networks” [Neural Networks Volume 168, November 2023, Pages 394–404](S0893608023005191)(10.1016/j.neunet.2023.09.025)', Neural Networks, 171, pp. 144, http://dx.doi.org/10.1016/j.neunet.2023.11.061
    Journal articles | 2024
    Jiang Y; Shen Y; Wang Y; Ding Q, 2024, 'Automatic recognition of white blood cell images with memory efficient superpixel metric GNN: SMGNN', Mathematical Biosciences and Engineering, 21, pp. 2163 - 2188, http://dx.doi.org/10.3934/mbe.2024095
    Journal articles | 2024
    Zhou B; Li R; Zheng X; Wang YG; Gao J, 2024, 'Graph Denoising with Framelet Regularizers', IEEE Transactions on Pattern Analysis and Machine Intelligence, http://dx.doi.org/10.1109/TPAMI.2024.3393131
    Journal articles | 2023
    Chen H; Wang YG; Xiong H, 2023, 'Lower and upper bounds for numbers of linear regions of graph convolutional networks', Neural Networks, 168, pp. 394 - 404, http://dx.doi.org/10.1016/j.neunet.2023.09.025
    Journal articles | 2023
    Jiang Y; Ding Q; Wang YG; Liò P; Zhang X, 2023, 'VISION GRAPH U-NET: GEOMETRIC LEARNING ENHANCED ENCODER FOR MEDICAL IMAGE SEGMENTATION AND RESTORATION', Inverse Problems and Imaging, 2023, http://dx.doi.org/10.3934/ipi.2023049
    Journal articles | 2023
    Li M; Kang L; Xiong Y; Wang YG; Fan G; Tan P; Hong L, 2023, 'SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering', Journal of Cheminformatics, 15, http://dx.doi.org/10.1186/s13321-023-00688-x
    Journal articles | 2023
    Liu Y; Pan S; Wang YG; Xiong F; Wang L; Chen Q; Lee VCS, 2023, 'Anomaly Detection in Dynamic Graphs via Transformer', IEEE Transactions on Knowledge and Data Engineering, 35, pp. 12081 - 12094, http://dx.doi.org/10.1109/TKDE.2021.3124061
    Journal articles | 2023
    Wang YG; Womersley RS; Wu HT; Yu WH, 2023, 'Numerical computation of triangular complex spherical designs with small mesh ratio', Journal of Computational and Applied Mathematics, 421, http://dx.doi.org/10.1016/j.cam.2022.114796
    Journal articles | 2023
    Zheng X; Zhou B; Li M; Wang YG; Gao J, 2023, 'MATHNET: Haar-like wavelet multiresolution analysis for graph representation learning', Knowledge-Based Systems, 273, http://dx.doi.org/10.1016/j.knosys.2023.110609
    Journal articles | 2022
    Montúfar G; Wang YG, 2022, 'Distributed Learning via Filtered Hyperinterpolation on Manifolds', Foundations of Computational Mathematics, 22, pp. 1219 - 1271, http://dx.doi.org/10.1007/s10208-021-09529-5
    Journal articles | 2022
    Wang Y; Wang YG; Hu C; Li M; Fan Y; Otter N; Sam I; Gou H; Hu Y; Kwok T; Zalcberg J; Boussioutas A; Daly RJ; Montúfar G; Liò P; Xu D; Webb GI; Song J, 2022, 'Cell graph neural networks enable the precise prediction of patient survival in gastric cancer', npj Precision Oncology, 6, http://dx.doi.org/10.1038/s41698-022-00285-5
    Journal articles | 2022
    Zheng X; Zhou B; Wang YG; Zhuang X, 2022, 'Decimated Framelet System on Graphs and Fast G-Framelet Transforms', Journal of Machine Learning Research, 23
    Journal articles | 2022
    Zhou B; Zheng X; Wang YG; Li M; Gao J, 2022, 'Embedding graphs on Grassmann manifold', Neural Networks, 152, pp. 322 - 331, http://dx.doi.org/10.1016/j.neunet.2022.05.001
    Journal articles | 2021
    Anh VV; Olenko A; Wang YG, 2021, 'Fractional stochastic partial differential equation for random tangent fields on the sphere', Theory of Probability and Mathematical Statistics, 104, pp. 3 - 22, http://dx.doi.org/10.1090/TPMS/1142
    Journal articles | 2021
    Bodnar C; Frasca F; Wang YG; Otter N; Montúfar G; Liò P; Bronstein M, 2021, 'Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks',
    Journal articles | 2021
    Hamann J; Le Gia QT; Sloan IH; Wang YG; Womersley RS, 2021, 'A new probe of Gaussianity and isotropy with application to cosmic microwave background maps', International Journal of Modern Physics C, 32, http://dx.doi.org/10.1142/S0129183121500844
    Journal articles | 2021
    Le Gia QT; Li M; Wang YG, 2021, 'Algorithm 1018: FaVeST-Fast Vector Spherical Harmonic Transforms', ACM Transactions on Mathematical Software, 47, http://dx.doi.org/10.1145/3458470
    Journal articles | 2021
    Ma Z; Xuan J; Wang YG; Li M; Liò P, 2021, 'Path integral based convolution and pooling for graph neural networksThis article is an updated version of: Ma Z, Xuan J, Wang Y G, Li M and Liò P 2020 Path integral based convolution and pooling for graph neural networks Advances in Neural Information Processing Systems vol 33 ed H Larochelle, M Ranzato, R Hadsell, M F Balcan and H Lin (New York: Curran Associates) pp 16421–33.', Journal of Statistical Mechanics: Theory and Experiment, 2021, http://dx.doi.org/10.1088/1742-5468/ac3ae4
    Journal articles | 2021
    Sourisseau M; Wang YG; Womersley RS; Wu HT; Yu WH, 2021, 'Improve concentration of frequency and time (ConceFT) by novel complex spherical designs', Applied and Computational Harmonic Analysis, 54, pp. 137 - 144, http://dx.doi.org/10.1016/j.acha.2021.02.003
    Journal articles | 2021
    Zheng X; Zhou B; Gao J; Wang YG; Lio P; Li M; Montufar G, 2021, 'How Framelets Enhance Graph Neural Networks',
    Journal articles | 2020
    Hallett N; Yi K; Dick J; Hodge C; Sutton G; Guang Wang Y; You J, 2020, 'Deep Learning Based Unsupervised and Semi-supervised Classification for Keratoconus', Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN48605.2020.9206694
    Journal articles | 2020
    Li M; Ma Z; Wang YG; Zhuang X, 2020, 'Fast Haar Transforms for Graph Neural Networks', Neural Networks, 128, pp. 188 - 198, http://dx.doi.org/10.1016/j.neunet.2020.04.028
    Journal articles | 2020
    Lin SB; Wang YG; Zhou DX, 2020, 'Distributed filtered hyperinterpolation for noisy data on the sphere', SIAM Journal on Numerical Analysis, 59, pp. 634 - 659, http://dx.doi.org/10.1137/19M1281095
    Journal articles | 2020
    Ma Z; Xuan J; Wang YG; Li M; Liò P, 2020, 'Path integral based convolution and pooling for graph neural networks', Advances in Neural Information Processing Systems, 2020-December
    Journal articles | 2020
    Sourisseau M; Wang YG; Womersley RS; Wu H-T; Yu W-H, 2020, 'Improve Concentration of Frequency and Time (Conceft) by Novel Complex Spherical Designs', , http://dx.doi.org/10.1101/2020.11.23.394007
    Journal articles | 2020
    Wang YG; Li M; Zheng M; Montufar G; Zhang X; Fan Y, 2020, 'Haar Graph Pooling', Proceedings of international conference on machine learning (ICML), 119, pp. 9952 - 9962, http://proceedings.mlr.press/v119/wang20m.html
    Journal articles | 2020
    Wang YG; Zhuang X, 2020, 'Tight framelets and fast framelet filter bank transforms on manifolds', Applied and Computational Harmonic Analysis, 48, pp. 64 - 95, http://dx.doi.org/10.1016/j.acha.2018.02.001
    Journal articles | 2020
    Yi K; Guo Y; Fan Y; Hamann J; Wang YG, 2020, 'Cosmo VAE: Variational Autoencoder for CMB Image Inpainting', Proceedings of the International Joint Conference on Neural Networks, http://dx.doi.org/10.1109/IJCNN48605.2020.9207123
    Journal articles | 2020
    Yi K; Guo Y; Hamann J; Fan Y; Wang Y, 2020, 'CosmoVAE: Variational Autoencoder for CMB Image Inpainting', IEEE Proceedings of the International Joint Conference on Neural Networks (IJCNN)
    Journal articles | 2020
    Zheng X; Zhou B; Wang YG; Zhuang X, 2020, 'Decimated Framelet System on Graphs and Fast G-Framelet Transforms', , http://arxiv.org/abs/2012.06922v2
    Journal articles | 2019
    Gia QTL; Li M; Wang YG, 2019, 'FaVeST: Fast Vector Spherical Harmonic Transforms', , http://arxiv.org/abs/1908.00041v3
    Journal articles | 2019
    Gia QTL; Sloan IH; Womersley RS; Wang YG, 2019, 'Isotropic sparse regularization for spherical harmonic representations of random fields on the sphere', Applied and Computational Harmonic Analysis, http://dx.doi.org/10.1016/j.acha.2019.01.005
    Journal articles | 2019
    Li M; Broadbridge P; Olenko A; Wang YG, 2019, 'Fast Tensor Needlet Transforms for Tangent Vector Fields on the Sphere', , http://arxiv.org/abs/1907.13339v1
    Journal articles | 2019
    Ma Z; Li M; Wang Y, 2019, 'PAN: Path Integral Based Convolution for Deep Graph Neural Networks', ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Representations (Oral), http://arxiv.org/abs/1904.10996v1
    Journal articles | 2019
    Wang YG; Womersley RS; Wu H-T; Yu W-H, 2019, 'Numerical computation of triangular complex spherical designs with small mesh ratio',
    Journal articles | 2018
    Anh VV; Broadbridge P; Olenko A; Wang YG, 2018, 'On approximation for fractional stochastic partial differential equations on the sphere', Stochastic Environmental Research and Risk Assessment, 32, pp. 2585 - 2603, http://dx.doi.org/10.1007/s00477-018-1517-1
    Journal articles | 2018
    Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2018, 'Random Point Sets on the Sphere-Hole Radii, Covering, and Separation', EXPERIMENTAL MATHEMATICS, 27, pp. 62 - 81, http://dx.doi.org/10.1080/10586458.2016.1226209
    Journal articles | 2018
    Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2018, 'Random Point Sets on the Sphere—Hole Radii, Covering, and Separation', Experimental Mathematics, 27, pp. 62 - 81, http://dx.doi.org/10.1080/10586458.2016.1226209
    Journal articles | 2018
    Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2018, 'Random Point Sets on the Sphere—Hole Radii, Covering, and Separation', Experimental Mathematics, 27, pp. 62 - 81, http://dx.doi.org/10.1080/10586458.2016.1226209
    Journal articles | 2018
    Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2018, 'Random Point Sets on the Sphere—Hole Radii, Covering, and Separation', Experimental Mathematics, 27, pp. 62 - 81, http://dx.doi.org/10.1080/10586458.2016.1226209
    Journal articles | 2017
    Le Gia QT; Sloan IH; Wang YG; Womersley RS, 2017, 'Needlet approximation for isotropic random fields on the sphere', Journal of Approximation Theory, 216, pp. 86 - 116, http://dx.doi.org/10.1016/j.jat.2017.01.001
    Journal articles | 2017
    Wang YG; Le Gia QT; Sloan IH; Womersley RS, 2017, 'Fully discrete needlet approximation on the sphere', Applied and Computational Harmonic Analysis, 43, pp. 292 - 316, http://dx.doi.org/10.1016/j.acha.2016.01.003
    Journal articles | 2016
    Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2016, 'Random Point Sets on the Sphere—Hole Radii, Covering, and Separation', Experimental Mathematics, pp. 1 - 20, http://dx.doi.org/10.1080/10586458.2016.1226209
    Journal articles | 2016
    Cao F; Wang D; Zhu H; Wang Y, 2016, 'An iterative learning algorithm for feedforward neural networks with random weights', Information Sciences, 328, pp. 546 - 557, http://dx.doi.org/10.1016/j.ins.2015.09.002
    Journal articles | 2016
    Wang Y, 2016, 'Filtered polynomial approximation on the sphere', Bulletin of the Australian Mathematical Society, 93, pp. 162 - 163, http://dx.doi.org/10.1017/S000497271500132X
    Journal articles | 2016
    Wang YG; Sloan IH; Womersley RS, 2016, 'Riemann Localisation on the Sphere', Journal of Fourier Analysis and Applications, 24, pp. 1 - 43, http://dx.doi.org/10.1007/s00041-016-9496-4
    Journal articles | 2015
    Brauchart JS; Dick J; Saff EB; Sloan IH; Wang YG; Womersley RS, 2015, 'Covering of spheres by spherical caps and worst-case error for equal weight cubature in Sobolev spaces', Journal of Mathematical Analysis and Applications, 431, pp. 782 - 811, http://dx.doi.org/10.1016/j.jmaa.2015.05.079
    Journal articles | 2015
    Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2015, 'Random Point Sets on the Sphere --- Hole Radii, Covering, and Separation',
    Journal articles | 2014
    Wang Y; Cao F, 2014, 'Approximation by semigroup of spherical operators', Frontiers of Mathematics in China, 9, pp. 387 - 416, http://dx.doi.org/10.1007/s11464-014-0361-y
    Journal articles | 2013
    Chen ZX; Zhu HY; Wang YG, 2013, 'A modified extreme learning machine with sigmoidal activation functions', Neural Computing and Applications, 22, pp. 541 - 550, http://dx.doi.org/10.1007/s00521-012-0860-2
    Journal articles | 2011
    Wang Y; Cao F; Yuan Y, 2011, 'A study on effectiveness of extreme learning machine', Neurocomputing, 74, pp. 2483 - 2490, http://dx.doi.org/10.1016/j.neucom.2010.11.030
    Journal articles | 2011
    Wang Y; Cao F, 2011, 'Approximation by Boolean sums of Jackson operators on the sphere', Journal of Computational Analysis and Applications, 13, pp. 830 - 842
    Journal articles | 2011
    Yuan Y; Wang Y; Cao F, 2011, 'Optimization approximation solution for regression problem based on extreme learning machine', Neurocomputing, 74, pp. 2475 - 2482, http://dx.doi.org/10.1016/j.neucom.2010.12.037
    Journal articles | 2009
    Cao F; Wang Y, 2009, 'The direct and converse inequalities for jackson-type operators on spherical cap', Journal of Inequalities and Applications, 2009, pp. 205298, http://dx.doi.org/10.1155/2009/205298
  • Working Papers | 2022
    Yi K; Chen J; Zhou B; Lio P; Fan Y; Hamann J, 2022, Approximate Equivariance SO(3) Needlet Convolution, http://dx.doi.org, https://arxiv.org/abs/2206.10385
    Working Papers | 2020
    Wang YG; Li M; Ma Z; Montufar G; Zhuang X; Fan Y, 2020, Haar graph pooling, http://dx.doi.org
    Working Papers | 2019
    Hamann J; Gia QTL; Sloan IH; Wang YG; Womersley RS, 2019, A New Probe of Gaussianity and Isotropy applied to the CMB Maps, http://dx.doi.org, http://arxiv.org/abs/1911.11442v2
  • Conference Papers | 2023
    Li M; Sonoda S; Cao F; Wang YG; Liang J, 2023, 'How Powerful are Shallow Neural Networks with Bandlimited Random Weights?', in Proceedings of Machine Learning Research, pp. 19360 - 19384
    Preprints | 2023
    Liu X; Zhou B; Zhang C; Wang YG, 2023, Framelet Message Passing, , http://arxiv.org/abs/2302.14806v1
    Conference Papers | 2023
    Shen Y; Zhou B; Xiong X; Gao R; Wang YG, 2023, 'How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images', in Proceedings - 2023 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023, pp. 2227 - 2230, http://dx.doi.org/10.1109/BIBM58861.2023.10385379
    Conference Papers | 2023
    Yi K; Zhou B; Shen Y; Liò P; Wang YG, 2023, 'Graph Denoising Diffusion for Inverse Protein Folding', in Advances in Neural Information Processing Systems
    Preprints | 2023
    Yi K; Zhou B; Shen Y; Liò P; Wang YG, 2023, Graph Denoising Diffusion for Inverse Protein Folding, , http://arxiv.org/abs/2306.16819v2
    Conference Papers | 2023
    Zhou B; Jiang Y; Wang Y; Liang J; Gao J; Pan S; Zhang X, 2023, 'Robust Graph Representation Learning for Local Corruption Recovery', in ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023, pp. 438 - 448, http://dx.doi.org/10.1145/3543507.3583399
    Conference Papers | 2022
    Banerjee PK; Karhadkar K; Wang YG; Alon U; Montufar G, 2022, 'Oversquashing in GNNs through the lens of information contraction and graph expansion', in 2022 58th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2022, http://dx.doi.org/10.1109/Allerton49937.2022.9929363
    Preprints | 2022
    Chen H; Wang YG; Xiong H, 2022, Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks, , http://arxiv.org/abs/2206.00228v1
    Preprints | 2022
    Shen Y; Zhou B; Xiong X; Gao R; Wang YG, 2022, How GNNs Facilitate CNNs in Mining Geometric Information from Large-Scale Medical Images, , http://arxiv.org/abs/2206.07599v1
    Preprints | 2022
    Wang Y; Yi K; Liu X; Wang YG; Jin S, 2022, ACMP: Allen-Cahn Message Passing for Graph Neural Networks with Particle Phase Transition, , http://arxiv.org/abs/2206.05437v3
    Preprints | 2022
    Zhou B; Jiang Y; Wang YG; Liang J; Gao J; Pan S; Zhang X, 2022, Robust Graph Representation Learning for Local Corruption Recovery, , http://arxiv.org/abs/2202.04936v4
    Conference Papers | 2022
    Zhou B; Liu X; Liu Y; Huang Y; Liò P; Wang YG, 2022, 'Well-conditioned Spectral Transforms for Dynamic Graph Representation', in Proceedings of Machine Learning Research
    Conference Papers | 2021
    Bodnar C; Frasca F; Otter N; Wang YG; Liò P; Montúfar G; Bronstein M, 2021, 'Weisfeiler and Lehman Go Cellular: CW Networks', in Advances in Neural Information Processing Systems, pp. 2625 - 2640
    Conference Papers | 2021
    Bodnar C; Frasca F; Wang YG; Otter N; Montúfar G; Liò P; Bronstein MM, 2021, 'Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks', in Proceedings of Machine Learning Research, pp. 1026 - 1037
    Conference Papers | 2021
    Zheng X; Zhou B; Gao J; Wang YG; Liò P; Li M; Montúfar G, 2021, 'How Framelets Enhance Graph Neural Networks', in Proceedings of Machine Learning Research, pp. 12761 - 12771
    Preprints | 2021
    Zhou B; Li R; Zheng X; Wang YG; Gao J, 2021, Graph Denoising with Framelet Regularizer, , http://arxiv.org/abs/2111.03264v1
    Preprints | 2021
    Zhou B; Liu X; Liu Y; Huang Y; Liò P; Wang Y, 2021, Spectral Transform Forms Scalable Transformer, , http://arxiv.org/abs/2111.07602v1
    Conference Papers | 2019
    Wang YG; Zhuang X, 2019, 'Tight framelets on graphs for multiscale data analysis', in Proceedings of SPIE - The International Society for Optical Engineering, http://dx.doi.org/10.1117/12.2528414