| 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 | 1338 | 2018 |
| Simple baseline for visual question answering B Zhou, Y Tian, S Sukhbaatar, A Szlam, R Fergus arXiv preprint arXiv:1512.02167, 2015 | 386 | 2015 |
| Single image 3d interpreter network J Wu, T Xue, JJ Lim, Y Tian, JB Tenenbaum, A Torralba, WT Freeman Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 362 | 2016 |
| Learning to Perform Local Rewriting for Combinatorial Optimization X Chen, Y Tian NeurIPS 2019, 2019 | 289 | 2019 |
| 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 | 275 | 2020 |
| Training agent for first-person shooter game with actor-critic curriculum learning Y Wu, Y Tian ICLR 2017, 2017 | 258 | 2017 |
| 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 | 252* | 2017 |
| 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 | 234 | 2018 |
| Building Generalizable Agents with a Realistic and Rich 3D Environment Y Wu, Y Wu, G Gkioxari, Y Tian ICLR workshop 2018, 2018 | 232 | 2018 |
| Understanding self-supervised Learning Dynamics without Contrastive Pairs Y Tian, X Chen, S Ganguli ICML 2021, 2021 | 231 | 2021 |
| 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 | 230 | 2017 |
| 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 | 216 | 2019 |
| Understanding dimensional collapse in contrastive self-supervised learning L Jing, P Vincent, Y LeCun, Y Tian ICLR 2022, 2021 | 214 | 2021 |
| Algorithmic Framework for Model-based Reinforcement Learning with Theoretical Guarantees H Xu, Y Li, Y Tian, T Darrell, T Ma ICLR 2019, 2018 | 213* | 2018 |
| 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 | 188 | 2007 |
| Exploring the spatial hierarchy of mixture models for human pose estimation Y Tian, CL Zitnick, SG Narasimhan Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 181 | 2012 |
| Semantic amodal segmentation Y Zhu, Y Tian, D Mexatas, P Dollįr CVPR 2017, 2015 | 155 | 2015 |
| 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 | 140 | 2017 |
| ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero Y Tian, J Ma, Q Gong, S Sengupta, Z Chen, J Pinkerton, CL Zitnick ICML 2019, 2019 | 137* | 2019 |
| When is a Convolutional Filter Easy to Learn? SS Du, JD Lee, Y Tian ICLR 2018, 2017 | 131 | 2017 |
Srinivasa NarasimhanProfessor of Robotics, Carnegie Mellon universityVerified email at andrew.cmu.edu
