By Dr Yu Guang Wang

Book Chapters

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

Wang YG; Zhu H, 2018, 'Analysis of framelet transforms on a simplex', in Contemporary Computational Mathematics A Celebration of the 80th Birthday of Ian Sloan, Springer Nature, pp. 1175 - 1189, http://dx.doi.org/10.1007/978-3-319-72456-0_54

Journal articles

Liu X; Zhou B; Zhang C; Wang YG, 2025, 'Framelet message passing', Applied and Computational Harmonic Analysis, 78, http://dx.doi.org/10.1016/j.acha.2025.101773

Sun X; Wang YG; Shen Y, 2025, 'A multimodal deep learning framework for enzyme turnover prediction with missing modality', Computers in Biology and Medicine, 193, http://dx.doi.org/10.1016/j.compbiomed.2025.110348

Yi K; Fan Y; Hamann J; Liò P; Wang YG, 2024, 'ABCMB: deep delensing assisted likelihood-free inference from CMB polarization maps', Machine Learning Science and Technology, 5, http://dx.doi.org/10.1088/2632-2153/ad9af9

Gao R; Yuan X; Ma Y; Wei T; Johnston L; Shao Y; Lv W; Zhu T; Zhang Y; Zheng J; Chen G; Sun J; Wang YG; Yu Z, 2024, 'Harnessing TME depicted by histological images to improve cancer prognosis through a deep learning system', Cell Reports Medicine, 5, http://dx.doi.org/10.1016/j.xcrm.2024.101536

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

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

Zhou B; Li R; Zheng X; Wang YG; Gao J, 2024, 'Graph Denoising With Framelet Regularizers', IEEE Transactions on Pattern Analysis and Machine Intelligence, 46, pp. 7606 - 7617, http://dx.doi.org/10.1109/TPAMI.2024.3393131

Duan W; Lu J; Wang YG; Xuan J, 2024, 'Layer-diverse Negative Sampling for Graph Neural Networks', Transactions on Machine Learning Research, 2024

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

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

Wang YG; Womersley RS; Wu H-T; Yu W-H, 2019, 'Numerical computation of triangular complex spherical designs with small mesh ratio',

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

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

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

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

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

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

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

Brauchart JS; Reznikov AB; Saff EB; Sloan IH; Wang YG; Womersley RS, 2015, 'Random Point Sets on the Sphere --- Hole Radii, Covering, and Separation',

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

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

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

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

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

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

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

Conference Papers

Liu Y; Chen Z; Wang YG; Shen Y, 2025, 'AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein Engineering', in Proceedings International Conference on Computational Linguistics Coling, pp. 422 - 430

Huang K; Wang YG; Li M; Liò P, 2024, 'How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing', in Proceedings of Machine Learning Research, PMLR, Vienna, Austria, pp. 20310 - 20330, presented at 41st International Conference on Machine Learning, Vienna, Austria, 21 July 2024, https://proceedings.mlr.press/v235/huang24z.html

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