Mingming Gong
Title
Cited by
Cited by
Year
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
6172018
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
5302018
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
1922016
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
1402018
Multi-source domain adaptation: A causal view
K Zhang, M Gong, B Schölkopf
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
1132015
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
952017
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
692018
Local metric learning for exemplar-based object detection
X You, Q Li, D Tao, W Ou, M Gong
IEEE Transactions on Circuits and Systems for Video Technology 24 (8), 1265-1276, 2014
642014
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
632019
Large-cone nonnegative matrix factorization
T Liu, M Gong, D Tao
IEEE transactions on neural networks and learning systems 28 (9), 2129-2142, 2016
632016
Causal inference by identification of vector autoregressive processes with hidden components
P Geiger, K Zhang, B Schoelkopf, M Gong, D Janzing
International Conference on Machine Learning, 1917-1925, 2015
562015
Discovering Temporal Causal Relations from Subsampled Data.
M Gong, K Zhang, B Schoelkopf, D Tao, P Geiger
ICML, 1898-1906, 2015
542015
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
472019
Domain generalization via conditional invariant representations
Y Li, M Gong, X Tian, T Liu, D Tao
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
452018
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
382018
Learning the implicit strain reconstruction in ultrasound elastography using privileged information
Z Gao, S Wu, Z Liu, J Luo, H Zhang, M Gong, S Li
Medical image analysis 58, 101534, 2019
332019
Label-noise robust domain adaptation
X Yu, T Liu, M Gong, K Zhang, K Batmanghelich, D Tao
International Conference on Machine Learning, 10913-10924, 2020
28*2020
Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results.
K Zhang, M Gong, J Ramsey, K Batmanghelich, P Spirtes, C Glymour
UAI, 1063-1072, 2018
26*2018
An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption
X Yu, T Liu, M Gong, K Batmanghelich, D Tao
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
262018
Causal discovery from temporally aggregated time series
M Gong, K Zhang, B Schölkopf, C Glymour, D Tao
Uncertainty in artificial intelligence: proceedings of the... conference …, 2017
262017
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Articles 1–20