| Improving the robustness of deep neural networks via stability training S Zheng, Y Song, T Leung, I Goodfellow Proceedings of the ieee conference on computer vision and pattern …, 2016 | 529 | 2016 |
| Long-term forecasting using tensor-train rnns R Yu, S Zheng, A Anandkumar, Y Yue Arxiv, 2017 | 111 | 2017 |
| Novel deep learning methods for track reconstruction S Farrell, P Calafiura, M Mudigonda, D Anderson, JR Vlimant, S Zheng, ... arXiv preprint arXiv:1810.06111, 2018 | 88 | 2018 |
| The ai economist: Improving equality and productivity with ai-driven tax policies S Zheng, A Trott, S Srinivasa, N Naik, M Gruesbeck, DC Parkes, R Socher arXiv preprint arXiv:2004.13332, 2020 | 82 | 2020 |
| Generating long-term trajectories using deep hierarchical networks S Zheng, Y Yue, J Hobbs Advances in Neural Information Processing Systems 29, 2016 | 81 | 2016 |
| Naomi: Non-autoregressive multiresolution sequence imputation Y Liu, R Yu, S Zheng, E Zhan, Y Yue Advances in neural information processing systems 32, 2019 | 58 | 2019 |
| Robustness gym: Unifying the nlp evaluation landscape K Goel, N Rajani, J Vig, S Tan, J Wu, S Zheng, C Xiong, M Bansal, C Ré arXiv preprint arXiv:2101.04840, 2021 | 56 | 2021 |
| Keeping your distance: Solving sparse reward tasks using self-balancing shaped rewards A Trott, S Zheng, C Xiong, R Socher Advances in Neural Information Processing Systems 32, 2019 | 55 | 2019 |
| Generating multi-agent trajectories using programmatic weak supervision E Zhan, S Zheng, Y Yue, L Sha, P Lucey arXiv preprint arXiv:1803.07612, 2018 | 48 | 2018 |
| Long-term forecasting using higher order tensor RNNs R Yu, S Zheng, A Anandkumar, Y Yue arXiv preprint arXiv:1711.00073, 2017 | 43 | 2017 |
| The HEP. TrkX Project: deep neural networks for HL-LHC online and offline tracking S Farrell, D Anderson, P Calafiura, G Cerati, L Gray, J Kowalkowski, ... EPJ Web of Conferences 150, 00003, 2017 | 40 | 2017 |
| Generative multi-agent behavioral cloning E Zhan, S Zheng, Y Yue, L Sha, P Lucey arXiv, 2018 | 28 | 2018 |
| The HEP. TrkX project: Deep learning for particle tracking A Tsaris, D Anderson, J Bendavid, P Calafiura, G Cerati, J Esseiva, ... Journal of Physics: Conference Series 1085 (4), 042023, 2018 | 22 | 2018 |
| Fine-grained retrieval of sports plays using tree-based alignment of trajectories L Sha, P Lucey, S Zheng, T Kim, Y Yue, S Sridharan arXiv preprint arXiv:1710.02255, 2017 | 21 | 2017 |
| On the generalization gap in reparameterizable reinforcement learning H Wang, S Zheng, C Xiong, R Socher International Conference on Machine Learning, 6648-6658, 2019 | 18 | 2019 |
| Detecting adversarial examples via neural fingerprinting S Dathathri, S Zheng, T Yin, RM Murray, Y Yue arXiv preprint arXiv:1803.03870, 2018 | 17 | 2018 |
| Learning chaotic dynamics using tensor recurrent neural networks R Yu, S Zheng, Y Liu Proceedings of the ICML 17, 2017 | 16 | 2017 |
| Screening of heterogeneous surfaces: charge renormalization of Janus particles N Boon, EC Gallardo, S Zheng, E Eggen, M Dijkstra, R Van Roij Journal of Physics: Condensed Matter 22 (10), 104104, 2010 | 15 | 2010 |
| Learning world graphs to accelerate hierarchical reinforcement learning W Shang, A Trott, S Zheng, C Xiong, R Socher arXiv preprint arXiv:1907.00664, 2019 | 13 | 2019 |
| Simulation intelligence: Towards a new generation of scientific methods A Lavin, H Zenil, B Paige, D Krakauer, J Gottschlich, T Mattson, ... arXiv preprint arXiv:2112.03235, 2021 | 12 | 2021 |
