Mingming Gong 个人学术档案

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	总计	2019 年至今
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Dacheng TaoNanyang Technological University在 ntu.edu.sg 的电子邮件经过验证
Tongliang LiuDirector, Sydney AI Centre, University of Sydney & Mohamed bin Zayed University of AI在 sydney.edu.au 的电子邮件经过验证
Kun ZhangCarnegie Mellon University & Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)在 cmu.edu 的电子邮件经过验证
Kayhan BatmanghelichAssistant Professor, Boston University在 bu.edu 的电子邮件经过验证
Bo HanHKBU / RIKEN在 comp.hkbu.edu.hk 的电子邮件经过验证
Gang NiuRIKEN Center for Advanced Intelligence Project在 riken.jp 的电子邮件经过验证
Chaohui WangLaboratoire d'Informatique Gaspard-Monge | Université Gustave Eiffel - CNRS - Ecole de Ponts在 u-pem.fr 的电子邮件经过验证
Biwei HuangUCSD在 andrew.cmu.edu 的电子邮件经过验证
Clark GlymourCarnegie Mellon University在 andrew.cmu.edu 的电子邮件经过验证
Xiaobo XiaPh.D. student, The University of Sydney在 uni.sydney.edu.au 的电子邮件经过验证
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETH在 tuebingen.mpg.de 的电子邮件经过验证
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of Tokyo在 k.u-tokyo.ac.jp 的电子邮件经过验证
Shanshan ZhaoAlibaba在 uni.sydney.edu.au 的电子邮件经过验证
Yu YaoLecturer in the University of Sydney在 sydney.edu.au 的电子邮件经过验证
Nannan WangProfessor, Xidian University在 xidian.edu.cn 的电子邮件经过验证
bo duSchool of Computer Science, Wuhan University在 whu.edu.cn 的电子邮件经过验证
Yanwu XuBoston University在 bu.edu 的电子邮件经过验证
Zhaoqing Wang (Derrick)Ph.D., Sydney AI Centre, University of Sydney在 uni.sydney.edu.au 的电子邮件经过验证
Xiyu YuAmap在 uni.sydney.edu.au 的电子邮件经过验证
Petar StojanovBroad Institute of MIT and Harvard在 broadinstitute.org 的电子邮件经过验证

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Mingming Gong

University of Melbourne & Mohamed bin Zayed University of Artificial Intelligence

在 unimelb.edu.au 的电子邮件经过验证 - 首页

Causal Inference Machine Learning Computer Vision


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
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	1922	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	1900	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	743	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	398	2016
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	278	2022
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	276	2020
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	235	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	233	2020
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	226	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	223	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	217	2018
Multi-source domain adaptation: A causal view K Zhang, M Gong, B Schölkopf Twenty-ninth AAAI conference on artificial intelligence, 2015	216	2015
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	209	2019
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	209	2017
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	206	2018
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	182	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	151	2021
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels X Xia, T Liu, B Han, M Gong, J Yu, G Niu, M Sugiyama arXiv preprint arXiv:2106.00445, 2021	124	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	110	2018
Discovering Temporal Causal Relations from Subsampled Data. M Gong, K Zhang, B Schoelkopf, D Tao, P Geiger ICML, 1898-1906, 2015	101	2015

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