| SNAS: stochastic neural architecture search S Xie, H Zheng, C Liu, L Lin International Conference on Learning Representations (ICLR) 2019, 2018 | 1152 | 2018 |
| DSNAS: Direct Neural Architecture Search without Parameter Retraining S Hu*, S Xie*, H Zheng, C Liu, J Shi, X Liu, D Lin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 159 | 2020 |
| Graph-guided Architecture Search for Real-time Semantic Segmentation P Lin, P Sun, G Cheng, S Xie, X Li, J Shi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 117 | 2019 |
| Latent Diffusion Energy-Based Model for Interpretable Text Modeling P Yu, S Xie, X Ma, B Jia, B Pang, R Gao, Y Zhu, SC Zhu, YN Wu International Conference on Machine Learning, 25702-25720, 2022 | 83 | 2022 |
| Unsupervised foreground extraction via deep region competition P Yu, S Xie, X Ma, Y Zhu, YN Wu, SC Zhu Advances in Neural Information Processing Systems 34, 14264-14279, 2021 | 39 | 2021 |
| Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning C Zhang*, S Xie*, B Jia*, YN Wu, SC Zhu, Y Zhu 17th European Conference on Computer Vision (ECCV 2022), 692--709, 2022 | 36 | 2022 |
| Learning a Decision Module by Imitating Drivers' Control Behaviors J Huang*, S Xie*, J Sun, Q Ma, C Liu, J Shi, D Lin, B Zhou 4th Conference on Robot Learning (CoRL 2020), 2019 | 30 | 2019 |
| HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving S Xie, X Ma, P Yu, Y Zhu, YN Wu, SC Zhu arXiv preprint arXiv:2102.11344, 2020 | 20 | 2020 |
| Emergent Graphical Conventions in a Visual Communication Game S Qiu*, S Xie*, L Fan, T Gao, SC Zhu, Y Zhu Advances in Neural Information Processing Systems 35, 13119--13131, 2022 | 15 | 2022 |
| Learning energy-based prior model with diffusion-amortized mcmc P Yu, Y Zhu, S Xie, XS Ma, R Gao, SC Zhu, YN Wu Advances in Neural Information Processing Systems 36, 42717-42747, 2023 | 10 | 2023 |
| EM Distillation for One-step Diffusion Models S Xie, Z Xiao, DP Kingma, T Hou, YN Wu, KP Murphy, T Salimans, ... arXiv preprint arXiv:2405.16852, 2024 | 9 | 2024 |
| NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning S Xie, J Huang, L Lei, C Liu, Z Ma, W Zhang, L Lin International Conference on Learning Representations (ICLR) 2019, 2018 | 9 | 2018 |
| COAT: Measuring Object Compositionality in Emergent Representations. S Xie, AS Morcos, SC Zhu, R Vedantam ICML, 24388-24413, 2022 | 8 | 2022 |
| Understanding the wiring evolution in differentiable neural architecture search S Xie*, S Hu*, X Wang, C Liu, J Shi, X Liu, D Lin International Conference on Artificial Intelligence and Statistics (AISTATS), 2020 | 8 | 2020 |
| Learning non-Markovian Decision-Making from State-only Sequences A Qin, F Gao, Q Li, SC Zhu, S Xie Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
| Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference D Kong, D Xu, M Zhao, B Pang, J Xie, A Lizarraga, Y Huang, S Xie, ... The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | 2* | 2024 |
| Scalable Language Models with Posterior Inference of Latent Thought Vectors D Kong, M Zhao, D Xu, B Pang, S Wang, E Honig, Z Si, C Li, J Xie, S Xie, ... arXiv preprint arXiv:2502.01567, 2025 | | 2025 |
| A Generative Account of Latent Abstractions S Xie University of California, Los Angeles, 2024 | | 2024 |
song-chun zhuProfessor of Statistics and Computer Science, UCLA確認したメール アドレス: stat.ucla.edu