| Learning to decompose and disentangle representations for video prediction JT Hsieh, B Liu, DA Huang, LF Fei-Fei, JC Niebles Advances in neural information processing systems 31, 2018 | 340 | 2018 |
| Spatiotemporal relationship reasoning for pedestrian intent prediction B Liu, E Adeli, Z Cao, KH Lee, A Shenoi, A Gaidon, JC Niebles IEEE Robotics and Automation Letters 5 (2), 3485-3492, 2020 | 152 | 2020 |
| Transformers learn shortcuts to automata B Liu, JT Ash, S Goel, A Krishnamurthy, C Zhang arXiv preprint arXiv:2210.10749, 2022 | 117 | 2022 |
| A computer vision system for deep learning-based detection of patient mobilization activities in the ICU S Yeung, F Rinaldo, J Jopling, B Liu, R Mehra, NL Downing, M Guo, ... NPJ digital medicine 2 (1), 11, 2019 | 112 | 2019 |
| Temporal modular networks for retrieving complex compositional activities in videos B Liu, S Yeung, E Chou, DA Huang, L Fei-Fei, JC Niebles Proceedings of the European Conference on Computer Vision (ECCV), 552-568, 2018 | 86 | 2018 |
| Exposing attention glitches with flip-flop language modeling B Liu, J Ash, S Goel, A Krishnamurthy, C Zhang Advances in Neural Information Processing Systems 36, 2024 | 24 | 2024 |
| Tinygsm: achieving> 80% on gsm8k with small language models B Liu, S Bubeck, R Eldan, J Kulkarni, Y Li, A Nguyen, R Ward, Y Zhang arXiv preprint arXiv:2312.09241, 2023 | 19 | 2023 |
| Analyzing and improving the optimization landscape of noise-contrastive estimation B Liu, E Rosenfeld, P Ravikumar, A Risteski arXiv preprint arXiv:2110.11271, 2021 | 17 | 2021 |
| Spatiotemporal relationship reasoning for pedestrian intent prediction E Adeli-mosabbeb, K Lee, A Gaidon, B Liu, Z Cao, JC Niebles US Patent 11,205,082, 2021 | 14 | 2021 |
| 3d point cloud-based visual prediction of icu mobility care activities B Liu, M Guo, E Chou, R Mehra, S Yeung, NL Downing, F Salipur, ... Machine learning for healthcare conference, 17-29, 2018 | 14 | 2018 |
| Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars K Wen, Y Li, B Liu, A Risteski Advances in Neural Information Processing Systems 36, 2024 | 13* | 2024 |
| Masked prediction tasks: a parameter identifiability view B Liu, D Hsu, P Ravikumar, A Risteski arXiv preprint arXiv:2202.09305, 2022 | 10* | 2022 |
| Generalized boosting A Suggala, B Liu, P Ravikumar Advances in neural information processing systems 33, 8787-8797, 2020 | 8 | 2020 |
| Understanding augmentation-based self-supervised representation learning via rkhs approximation R Zhai, B Liu, A Risteski, Z Kolter, P Ravikumar arXiv preprint arXiv:2306.00788, 2023 | 5 | 2023 |
| Contrastive learning of strong-mixing continuous-time stochastic processes B Liu, P Ravikumar, A Risteski International Conference on Artificial Intelligence and Statistics, 3151-3159, 2021 | 5 | 2021 |
| Understanding augmentation-based self-supervised representation learning via rkhs approximation and regression R Zhai, B Liu, A Risteski, Z Kolter, P Ravikumar arXiv preprint arXiv:2306.00788, 2023 | 2 | 2023 |
| A Computer Vision System to Detect Bedside Patient Mobilization F Rinaldo, J Jopling, B Liu, R Mehra, L Downing, M Guo, G Bianconi, ... Nature Digital Medicine, 2019 | | 2019 |
| Progressive distillation improves feature learning via implicit curriculum A Panigrahi, B Liu, S Malladi, A Risteski, S Goel ICML 2024 Workshop on Mechanistic Interpretability, 0 | | |
| Augmentation Alone Leads to Generalization R Zhai, B Liu, A Risteski, JZ Kolter, PK Ravikumar ICLR 2024 Workshop on Reliable and Responsible Foundation Models, 0 | | |
| EE376A (Winter 2019) B Liu, JT Hsieh | | |
Li Fei-FeiProfessor of Computer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
