| Summary of chatgpt-related research and perspective towards the future of large language models Y Liu, T Han, S Ma, J Zhang, Y Yang, J Tian, H He, A Li, M He, Z Liu, Z Wu, ... Meta-Radiology, 100017, 2023 | 667 | 2023 |
| Exposure: A white-box photo post-processing framework Y Hu, H He, C Xu, B Wang, S Lin ACM Transactions on Graphics (TOG) 37 (2), 1-17, 2018 | 317 | 2018 |
| RF-based fall monitoring using convolutional neural networks Y Tian, GH Lee, H He, CY Hsu, D Katabi Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018 | 182 | 2018 |
| Extracting multi-person respiration from entangled RF signals S Yue, H He, H Wang, H Rahul, D Katabi Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018 | 181 | 2018 |
| Circuit-GNN: Graph neural networks for distributed circuit design G Zhang, H He, D Katabi International Conference on Machine Learning (ICML), 7364-7373, 2019 | 137 | 2019 |
| Learning compositional koopman operators for model-based control Y Li, H He, J Wu, D Katabi, A Torralba International Conference on Learning Representations (ICLR), 2020 | 124 | 2020 |
| Continuously indexed domain adaptation H Wang, H He, D Katabi International Conference on Machine Learning (ICML), 2020 | 123 | 2020 |
| Probgan: Towards probabilistic gan with theoretical guarantees H He, H Wang, GH Lee, Y Tian International Conference on Learning Representations (ICLR), 2018 | 54* | 2018 |
| From Bayesian sparsity to gated recurrent nets H He, B Xin, S Ikehata, D Wipf Advances in Neural Information Processing Systems (NeurIPS) 30, 2017 | 37 | 2017 |
| Understanding llms: A comprehensive overview from training to inference Y Liu, H He, T Han, X Zhang, M Liu, J Tian, Y Zhang, J Wang, X Gao, ... arXiv preprint arXiv:2401.02038, 2024 | 29 | 2024 |
| Graph-relational domain adaptation Z Xu, H He, GH Lee, Y Wang, H Wang International Conference on Learning Representations (ICLR), 2022 | 28 | 2022 |
| Indiscriminate poisoning attacks on unsupervised contrastive learning H He, K Zha, D Katabi International Conference on Learning Representations (ICLR), 2023 | 25 | 2023 |
| Training-free uncertainty estimation for dense regression: Sensitivity as a surrogate L Mi, H Wang, Y Tian, H He, NN Shavit Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 36 (9 …, 2022 | 23 | 2022 |
| Bidirectional inference networks: A class of deep bayesian networks for health profiling H Wang, C Mao, H He, M Zhao, TS Jaakkola, D Katabi Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 33 (01 …, 2019 | 23 | 2019 |
| Addressing feature suppression in unsupervised visual representations T Li, L Fan, Y Yuan, H He, Y Tian, R Feris, P Indyk, D Katabi Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 22* | 2023 |
| Controlling directions orthogonal to a classifier Y Xu, H He, T Shen, T Jaakkola International Conference on Learning Representations (ICLR), 2022 | 22 | 2022 |
| UST: Unifying spatio-temporal context for trajectory prediction in autonomous driving H He, H Dai, N Wang 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 22 | 2020 |
| CornerRadar: RF-based indoor localization around corners S Yue, H He, P Cao, K Zha, M Koizumi, D Katabi Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2022 | 17 | 2022 |
| Domain-indexing variational bayes: Interpretable domain index for domain adaptation Z Xu, GY Hao, H He, H Wang International Conference on Learning Representations (ICLR), 2023 | 14 | 2023 |
| Holistic evaluation of gpt-4v for biomedical imaging Z Liu, H Jiang, T Zhong, Z Wu, C Ma, Y Li, X Yu, Y Zhang, Y Pan, P Shu, ... arXiv preprint arXiv:2312.05256, 2023 | 9 | 2023 |
Dina KatabiThuan and Nicole Pham Professor, MIT在 ai.mit.edu 的电子邮件经过验证
