| Convolutional Networks with Dense Connectivity G Huang, Z Liu, G Pleiss, L Van Der Maaten, K Weinberger IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019 | 26247* | 2019 |
| Deep Networks with Stochastic Depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger European Conference on Computer Vision (ECCV), 646-661, 2016 | 1662 | 2016 |
| Learning efficient convolutional networks through network slimming Z Liu, J Li, Z Shen, G Huang, S Yan, C Zhang IEEE International Conference on Computer Vision (ICCV), 2736-2744, 2017 | 1550 | 2017 |
| Trends in extreme learning machines: A review G Huang, GB Huang, S Song, K You Neural Networks 61, 32-48, 2015 | 1511 | 2015 |
| Rethinking the value of network pruning Z Liu, M Sun, T Zhou, G Huang, T Darrell International Conference on Learning Representations (ICLR), 2018 | 918 | 2018 |
| Semi-supervised and unsupervised extreme learning machines G Huang, S Song, JND Gupta, C Wu IEEE Transactions on Cybernetics 44 (12), 2405 - 2417, 2014 | 734 | 2014 |
| Snapshot ensembles: Train 1, get M for free G Huang, Y Li, G Pleiss, Z Liu, JE Hopcroft, KQ Weinberger International Conference on Learning Representations (ICLR), 2017 | 639 | 2017 |
| CondenseNet: An Efficient DenseNet using Learned Group Convolutions G Huang, S Liu, L van der Maaten, KQ Weinberger IEEE Conference on Pattern Recognition and Computer Vision (CVPR) 3 (12), 11, 2018 | 618 | 2018 |
| Multi-scale dense networks for resource efficient image classification G Huang, D Chen, T Li, F Wu, L van der Maaten, KQ Weinberger International Conference on Learning Representations (ICLR), 2018 | 554* | 2018 |
| Horizontal pyramid matching for person re-identification Y Fu, Y Wei, Y Zhou, H Shi, G Huang, X Wang, Z Yao, T Huang Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 33 …, 2019 | 297 | 2019 |
| Resource Aware Person Re-identification across Multiple Resolutions Y Wang, L Wang, Y You, X Zou, V Chen, S Li, G Huang, B Hariharan, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 8042-8051, 2018 | 230 | 2018 |
| An empirical study on evaluation metrics of generative adversarial networks Q Xu, G Huang, Y Yuan, C Guo, Y Sun, F Wu, K Weinberger arXiv preprint arXiv:1806.07755, 2018 | 212 | 2018 |
| Supervised word mover's distance G Huang, C Guo, MJ Kusner, Y Sun, F Sha, KQ Weinberger Advances in Neural Information Processing Systems (NIPS), 4862-4870, 2016 | 163 | 2016 |
| Densely connected convolutional networks. arXiv 2016 G Huang, Z Liu, L van der Maaten, KQ Weinberger arXiv preprint arXiv:1608.06993 1608, 2018 | 146 | 2018 |
| Memory-efficient implementation of densenets G Pleiss, D Chen, G Huang, T Li, L van der Maaten, KQ Weinberger Technical Report, 2017 | 144 | 2017 |
| Domain invariant and class discriminative feature learning for visual domain adaptation S Li, S Song, G Huang, Z Ding, C Wu IEEE transactions on image processing 27 (9), 4260-4273, 2018 | 137 | 2018 |
| Gradient boosted feature selection Z Xu, G Huang, KQ Weinberger, AX Zheng SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD …, 2014 | 133 | 2014 |
| Maaten Lvd, Weinberger KQ. Densely Connected Convolutional Networks G Huang, Z Liu 2017 IEEE conference on computer vision and pattern recognition (CVPR) 2261 …, 2017 | 107 | 2017 |
| Anytime stereo image depth estimation on mobile devices Y Wang, Z Lai, G Huang, BH Wang, L Van Der Maaten, M Campbell, ... 2019 International Conference on Robotics and Automation (ICRA), 5893-5900, 2019 | 103 | 2019 |
| Dynamic neural networks: A survey Y Han, G Huang, S Song, L Yang, H Wang, Y Wang IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 | 101 | 2021 |
Kilian WeinbergerCornell UniversityVerified email at cornell.edu
