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
5622018
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
4732018
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
1862016
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
1222018
Multi-source domain adaptation: A causal view
K Zhang, M Gong, B Schölkopf
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
1082015
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
842017
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
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
632014
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
612018
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
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
542019
Discovering Temporal Causal Relations from Subsampled Data.
M Gong, K Zhang, B Schoelkopf, D Tao, P Geiger
ICML, 1898-1906, 2015
522015
Domain generalization via conditional invariant representations
Y Li, M Gong, X Tian, T Liu, D Tao
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
422018
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
372019
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
372018
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
302019
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
27*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
242018
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
242017
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Articles 1–20