| 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 | 1643 | 2018 |
| Efficient streaming language models with attention sinks G Xiao, Y Tian, B Chen, S Han, M Lewis ICLR 2024, 2023 | 488 | 2023 |
| Learning to Perform Local Rewriting for Combinatorial Optimization X Chen, Y Tian NeurIPS 2019, 2019 | 440 | 2019 |
| Simple baseline for visual question answering B Zhou, Y Tian, S Sukhbaatar, A Szlam, R Fergus arXiv preprint arXiv:1512.02167, 2015 | 430 | 2015 |
| Understanding dimensional collapse in contrastive self-supervised learning L Jing, P Vincent, Y LeCun, Y Tian ICLR 2022, 2021 | 418 | 2021 |
| Extending context window of large language models via positional interpolation S Chen, S Wong, L Chen, Y Tian arXiv preprint arXiv:2306.15595, 2023 | 383 | 2023 |
| 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 | 373 | 2016 |
| A cookbook of self-supervised learning R Balestriero, M Ibrahim, V Sobal, A Morcos, S Shekhar, T Goldstein, ... arXiv preprint arXiv:2304.12210, 2023 | 372 | 2023 |
| 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 | 367 | 2020 |
| Understanding self-supervised Learning Dynamics without Contrastive Pairs Y Tian, X Chen, S Ganguli ICML 2021, 2021 | 338 | 2021 |
| H O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models Z Zhang, Y Sheng, T Zhou, T Chen, L Zheng, R Cai, Z Song, Y Tian, C Ré, ... NeurIPS 2023, 2023 | 331 | 2023 |
| 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 | 320 | 2018 |
| Training agent for first-person shooter game with actor-critic curriculum learning Y Wu, Y Tian ICLR 2017, 2017 | 286 | 2017 |
| Algorithmic Framework for Model-based Reinforcement Learning with Theoretical Guarantees H Xu, Y Li, Y Tian, T Darrell, T Ma ICLR 2019, 2018 | 284* | 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 | 277 | 2019 |
| 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 | 277* | 2017 |
| Deja vu: Contextual sparsity for efficient llms at inference time Z Liu, J Wang, T Dao, T Zhou, B Yuan, Z Song, A Shrivastava, C Zhang, ... International Conference on Machine Learning, 22137-22176, 2023 | 274 | 2023 |
| Building Generalizable Agents with a Realistic and Rich 3D Environment Y Wu, Y Wu, G Gkioxari, Y Tian ICLR workshop 2018, 2018 | 274 | 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 | 256 | 2017 |
| Semantic amodal segmentation Y Zhu, Y Tian, D Mexatas, P Dollár CVPR 2017, 2015 | 200 | 2015 |
Srinivasa NarasimhanU. A. and Helen Whitaker Professor of Robotics, Carnegie Mellon universityPreverjeni e-poštni naslov na andrew.cmu.edu
