| 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 | 44965 | 2017 |
| On calibration of modern neural networks C Guo, G Pleiss, Y Sun, KQ Weinberger International conference on machine learning, 1321-1330, 2017 | 5726 | 2017 |
| Distance metric learning for large margin nearest neighbor classification. KQ Weinberger, LK Saul Journal of machine learning research 10 (2), 2009 | 4832 | 2009 |
| Bertscore: Evaluating text generation with bert T Zhang, V Kishore, F Wu, KQ Weinberger, Y Artzi arXiv preprint arXiv:1904.09675, 2019 | 4116 | 2019 |
| Simplifying graph convolutional networks F Wu, A Souza, T Zhang, C Fifty, T Yu, K Weinberger International conference on machine learning, 6861-6871, 2019 | 3198 | 2019 |
| From word embeddings to document distances M Kusner, Y Sun, N Kolkin, K Weinberger International conference on machine learning, 957-966, 2015 | 2770 | 2015 |
| Deep networks with stochastic depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 2650 | 2016 |
| Distance metric learning for large margin nearest neighbor classification KQ Weinberger, J Blitzer, L Saul Advances in neural information processing systems 18, 2005 | 2447 | 2005 |
| Advances in neural information processing systems A Krizhevsky (No Title), 1097, 2012 | 2016 | 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 | 1414 | 2015 |
| Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul International journal of computer vision 70 (1), 77-90, 2006 | 1230 | 2006 |
| Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul CVPR 2, 988-995, 2004 | 1230 | 2004 |
| 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 | 1194 | 2009 |
| 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 | 1153 | 2018 |
| 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 | 1115 | 2019 |
| Marginalized denoising auto-encoders for nonlinear representations M Chen, K Weinberger, F Sha, Y Bengio International conference on machine learning, 1476-1484, 2014 | 1072 | 2014 |
| 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 | 1059 | 2017 |
| On fairness and calibration G Pleiss, M Raghavan, F Wu, J Kleinberg, KQ Weinberger Advances in neural information processing systems 30, 2017 | 968 | 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 | 953 | 2018 |
| Multi-scale dense networks for resource efficient image classification G Huang, D Chen, T Li, F Wu, L Van Der Maaten, KQ Weinberger arXiv preprint arXiv:1703.09844, 2017 | 795 | 2017 |
Gao Huang （黄高）Associate Professor, Tsinghua University在 tsinghua.edu.cn 的电子邮件经过验证
