Mingming Gong

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Dacheng TaoThe University of SydneyVerified email at sydney.edu.au
Tongliang LiuDirector, Sydney AI Centre, University of Sydney & Mohamed bin Zayed University of AIVerified email at sydney.edu.au
Kun ZhangCarnegie Mellon University & Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)Verified email at cmu.edu
Kayhan BatmanghelichAssistant Professor, Boston UniversityVerified email at bu.edu
Bo HanHKBU / RIKENVerified email at comp.hkbu.edu.hk
Chaohui WangLaboratoire d'Informatique Gaspard-Monge | Université Gustave Eiffel - CNRS - Ecole de PontsVerified email at u-pem.fr
Gang NiuRIKEN Center for Advanced Intelligence ProjectVerified email at riken.jp
Clark GlymourCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Shanshan ZhaoPhD; JD, previouslyVerified email at uni.sydney.edu.au
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerified email at tuebingen.mpg.de
Xiaobo XiaPh.D. student, The University of SydneyVerified email at uni.sydney.edu.au
Biwei HuangUCSDVerified email at andrew.cmu.edu
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Nannan WangProfessor, Xidian UniversityVerified email at xidian.edu.cn
bo duSchool of Computer Science, Wuhan UniversityVerified email at whu.edu.cn
Yanwu XuBoston UniversityVerified email at bu.edu
Xiyu YuAmapVerified email at uni.sydney.edu.au
Petar StojanovBroad Institute of MIT and HarvardVerified email at broadinstitute.org
Zhaoqing Wang (Derrick)Ph.D., Sydney AI Centre, University of SydneyVerified email at uni.sydney.edu.au
Qiang LiSenseTimeVerified email at comp.polyu.edu.hk

Mingming Gong

University of Melbourne

Verified email at unimelb.edu.au - Homepage

Causal Inference Machine Learning Computer Vision


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Deep Ordinal Regression Network for Monocular Depth Estimation H Fu, M Gong, C Wang, K Batmanghelich, D Tao Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018	1627	2018
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018	1613	2018
Deep Domain Generalization via Conditional Invariant Adversarial Networks Y Li, X Tian, M Gong, Y Liu, T Liu, K Zhang, D Tao Proceedings of the European Conference on Computer Vision (ECCV), 624-639, 2018	602	2018
Domain Adaptation with Conditional Transferable Components M Gong, K Zhang, T Liu, D Tao, C Glymour, B Schölkopf Proceedings of The 33rd International Conference on Machine Learning, 2839-2848, 2016	351	2016
Part-dependent label noise: Towards instance-dependent label noise X Xia, T Liu, B Han, N Wang, M Gong, H Liu, G Niu, D Tao, M Sugiyama Advances in Neural Information Processing Systems 33, 7597-7610, 2020	206	2020
Multi-source domain adaptation: A causal view K Zhang, M Gong, B Schölkopf Twenty-ninth AAAI conference on artificial intelligence, 2015	196	2015
A coarse-fine network for keypoint localization S Huang, M Gong, D Tao Proceedings of the IEEE International Conference on Computer Vision, 3028-3037, 2017	190	2017
Domain generalization via entropy regularization S Zhao, M Gong, T Liu, H Fu, D Tao Advances in Neural Information Processing Systems 33, 16096-16107, 2020	184	2020
Sub-center arcface: Boosting face recognition by large-scale noisy web faces J Deng, J Guo, T Liu, M Gong, S Zafeiriou European Conference on Computer Vision, 741-757, 2020	179	2020
Geometry-consistent generative adversarial networks for one-sided unsupervised domain mapping H Fu, M Gong, C Wang, K Batmanghelich, K Zhang, D Tao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	179	2019
Domain generalization via conditional invariant representations Y Li, M Gong, X Tian, T Liu, D Tao Thirty-Second AAAI Conference on Artificial Intelligence, 2018	178	2018
Dual t: Reducing estimation error for transition matrix in label-noise learning Y Yao, T Liu, B Han, M Gong, J Deng, G Niu, M Sugiyama Advances in Neural Information Processing Systems 33, 2020	174	2020
Geometry-aware symmetric domain adaptation for monocular depth estimation S Zhao, H Fu, M Gong, D Tao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	173	2019
Learning with biased complementary labels X Yu, T Liu, M Gong, D Tao Proceedings of the European Conference on Computer Vision (ECCV), 68-83, 2018	173	2018
Cris: Clip-driven referring image segmentation Z Wang, Y Lu, Q Li, X Tao, Y Guo, M Gong, T Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	144	2022
3d-future: 3d furniture shape with texture H Fu, R Jia, L Gao, M Gong, B Zhao, S Maybank, D Tao International Journal of Computer Vision, 1-25, 2021	115	2021
Adaptive context-aware multi-modal network for depth completion S Zhao, M Gong, H Fu, D Tao IEEE Transactions on Image Processing 30, 5264-5276, 2021	110	2021
Correcting the Triplet Selection Bias for Triplet Loss B Yu, T Liu, M Gong, C Ding, D Tao Proceedings of the European Conference on Computer Vision (ECCV), 71-87, 2018	99	2018
Discovering Temporal Causal Relations from Subsampled Data. M Gong, K Zhang, B Schoelkopf, D Tao, P Geiger ICML, 1898-1906, 2015	90	2015
Twin auxilary classifiers GAN M Gong, Y Xu, C Li, K Zhang, K Batmanghelich Advances in neural information processing systems, 1330-1339, 2019	78	2019

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