| Densely connected convolutional networks G Huang, Z Liu, L Van Der Maaten, KQ Weinberger Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 27018 | 2017 |
| Distance metric learning for large margin nearest neighbor classification. KQ Weinberger, LK Saul Journal of machine learning research 10 (2), 2009 | 4142 | 2009 |
| On calibration of modern neural networks C Guo, G Pleiss, Y Sun, KQ Weinberger International conference on machine learning, 1321-1330, 2017 | 2696 | 2017 |
| Distance metric learning for large margin nearest neighbor classification KQ Weinberger, J Blitzer, L Saul Advances in neural information processing systems 18, 2005 | 2325 | 2005 |
| From word embeddings to document distances M Kusner, Y Sun, N Kolkin, K Weinberger International conference on machine learning, 957-966, 2015 | 2038 | 2015 |
| Deep networks with stochastic depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger European conference on computer vision, 646-661, 2016 | 1723 | 2016 |
| Simplifying graph convolutional networks F Wu, A Souza, T Zhang, C Fifty, T Yu, K Weinberger International conference on machine learning, 6861-6871, 2019 | 1277 | 2019 |
| Advances in neural information processing systems A Krizhevsky, I Sutskever, GE Hinton, F Pereira, CJC Burges, L Bottou, ... MIT Press 25, 1097-1105, 2012 | 1226 | 2012 |
| Compressing neural networks with the hashing trick W Chen, J Wilson, S Tyree, K Weinberger, Y Chen International conference on machine learning, 2285-2294, 2015 | 1168 | 2015 |
| Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul International journal of computer vision 70 (1), 77-90, 2006 | 1152 | 2006 |
| Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul CVPR 2, 988-995, 2004 | 1152 | 2004 |
| Bertscore: Evaluating text generation with bert T Zhang, V Kishore, F Wu, KQ Weinberger, Y Artzi arXiv preprint arXiv:1904.09675, 2019 | 1133 | 2019 |
| Feature hashing for large scale multitask learning K Weinberger, A Dasgupta, J Langford, A Smola, J Attenberg Proceedings of the 26th annual international conference on machine learning …, 2009 | 1007 | 2009 |
| Marginalized denoising autoencoders for domain adaptation M Chen, Z Xu, K Weinberger, F Sha arXiv preprint arXiv:1206.4683, 2012 | 870 | 2012 |
| Snapshot ensembles: Train 1, get m for free G Huang, Y Li, G Pleiss, Z Liu, JE Hopcroft, KQ Weinberger arXiv preprint arXiv:1704.00109, 2017 | 668 | 2017 |
| Condensenet: An efficient densenet using learned group convolutions G Huang, S Liu, L Van der Maaten, KQ Weinberger Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 639 | 2018 |
| Learning a kernel matrix for nonlinear dimensionality reduction KQ Weinberger, F Sha, LK Saul Proceedings of the twenty-first international conference on Machine learning …, 2004 | 627 | 2004 |
| Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving Y Wang, WL Chao, D Garg, B Hariharan, M Campbell, KQ Weinberger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 583 | 2019 |
| On fairness and calibration G Pleiss, M Raghavan, F Wu, J Kleinberg, KQ Weinberger Advances in neural information processing systems 30, 2017 | 551 | 2017 |
| Gpytorch: Blackbox matrix-matrix gaussian process inference with gpu acceleration J Gardner, G Pleiss, KQ Weinberger, D Bindel, AG Wilson Advances in neural information processing systems 31, 2018 | 505 | 2018 |
Gao Huang （黄高）Associate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
