| FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search B Wu, X Dai, P Zhang, Y Wang, F Sun, Y Wu, Y Tian, P Vajda, Y Jia, ... CVPR 2019, 2018 | 900 | 2018 |
| Simple baseline for visual question answering B Zhou, Y Tian, S Sukhbaatar, A Szlam, R Fergus arXiv preprint arXiv:1512.02167, 2015 | 341 | 2015 |
| Single image 3d interpreter network J Wu, T Xue, JJ Lim, Y Tian, JB Tenenbaum, A Torralba, WT Freeman European Conference on Computer Vision, 365-382, 2016 | 338 | 2016 |
| An analytical formula of population gradient for two-layered relu network and its applications in convergence and critical point analysis Y Tian Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 207* | 2017 |
| Building Generalizable Agents with a Realistic and Rich 3D Environment Y Wu, Y Wu, G Gkioxari, Y Tian ICLR workshop 2018, 2018 | 197 | 2018 |
| Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima SS Du, JD Lee, Y Tian, B Poczos, A Singh ICML 2018, 2017 | 196 | 2017 |
| Easyalbum: an interactive photo annotation system based on face clustering and re-ranking J Cui, F Wen, R Xiao, Y Tian, X Tang Proceedings of the SIGCHI conference on Human factors in computing systems …, 2007 | 183 | 2007 |
| Training agent for first-person shooter game with actor-critic curriculum learning Y Wu, Y Tian ICLR 2017, 2017 | 180 | 2017 |
| Exploring the spatial hierarchy of mixture models for human pose estimation Y Tian, CL Zitnick, SG Narasimhan European Conference on Computer Vision, 256-269, 2012 | 174 | 2012 |
| Fbnetv2: Differentiable neural architecture search for spatial and channel dimensions A Wan, X Dai, P Zhang, Z He, Y Tian, S Xie, B Wu, M Yu, T Xu, K Chen, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 166 | 2020 |
| Mixed precision quantization of convnets via differentiable neural architecture search B Wu, Y Wang, P Zhang, Y Tian, P Vajda, K Keutzer arXiv preprint arXiv:1812.00090, 2018 | 158 | 2018 |
| Algorithmic Framework for Model-based Reinforcement Learning with Theoretical Guarantees H Xu, Y Li, Y Tian, T Darrell, T Ma ICLR 2019, 2018 | 155* | 2018 |
| One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers AS Morcos, H Yu, M Paganini, Y Tian NeurIPS 2019, 2019 | 149 | 2019 |
| Learning to Perform Local Rewriting for Combinatorial Optimization X Chen, Y Tian NeurIPS 2019, 2019 | 146 | 2019 |
| ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games Y Tian, Q Gong, W Shang, Y Wu, L Zitnick NIPS 2017, 2017 | 127 | 2017 |
| Better computer go player with neural network and long-term prediction Y Tian, Y Zhu ICLR 2016, 2015 | 120 | 2015 |
| When is a Convolutional Filter Easy to Learn? SS Du, JD Lee, Y Tian ICLR 2018, 2017 | 119 | 2017 |
| A face annotation framework with partial clustering and interactive labeling Y Tian, W Liu, R Xiao, F Wen, X Tang 2007 IEEE conference on computer vision and pattern recognition, 1-8, 2007 | 117 | 2007 |
| Seeing through water: Image restoration using model-based tracking Y Tian, SG Narasimhan 2009 IEEE 12th International Conference on Computer Vision, 2303-2310, 2009 | 116 | 2009 |
| Semantic amodal segmentation Y Zhu, Y Tian, D Mexatas, P Dollįr CVPR 2017, 2015 | 107 | 2015 |
Srinivasa NarasimhanProfessor of Robotics, Carnegie Mellon universityVerified email at andrew.cmu.edu
