From Bayesian Sparsity to Gated Recurrent Nets. - Hao He 011; Bo Xin; Satoshi Ikehata; David P. Wipf (NIPS, 2017)

From Bayesian Sparsity to Gated Recurrent Nets. - Hao He 011; Bo Xin; David P. Wipf (CoRR, 2017)

RF-Based Fall Monitoring Using Convolutional Neural Networks. - Yonglong Tian; Guang-He Lee; Hao He 011; Chen-Yu Hsu 001; Dina Katabi (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2018)

Extracting Multi-Person Respiration from Entangled RF Signals. - Shichao Yue; Hao He 011; Hao Wang 014; Hariharan Rahul; Dina Katabi (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2018)

Exposure: A White-Box Photo Post-Processing Framework. - Yuanming Hu; Hao He 011; Chenxi Xu; Baoyuan Wang; Stephen Lin 001 (ACM Trans. Graph., 2018)

Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling. - Hao Wang 014; Chengzhi Mao; Hao He 011; Mingmin Zhao; Tommi S. Jaakkola; Dina Katabi (AAAI, 2019)

ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees. - Hao He 011; Hao Wang 014; Guang-He Lee; Yonglong Tian (ICLR (Poster), 2019)

Circuit-GNN: Graph Neural Networks for Distributed Circuit Design. - Guo Zhang 006; Hao He 011; Dina Katabi (ICML, 2019)

Learning Compositional Koopman Operators for Model-Based Control. - Yunzhu Li; Hao He 011; Jiajun Wu 001; Dina Katabi; Antonio Torralba 001 (ICLR, 2020)

Continuously Indexed Domain Adaptation. - Hao Wang 014; Hao He 011; Dina Katabi (ICML, 2020)

UST: Unifying Spatio-Temporal Context for Trajectory Prediction in Autonomous Driving. - Hao He 011; Hengchen Dai; Naiyan Wang (IROS, 2020)

Information-Preserving Contrastive Learning for Self-Supervised Representations. - Tianhong Li; Lijie Fan; Yuan Yuan 002; Hao He 011; Yonglong Tian; Dina Katabi (CoRR, 2020)

Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate. - Lu Mi; Hao Wang 014; Yonglong Tian; Hao He 011; Nir Shavit (AAAI, 2022)

CounTr: An End-to-End Transformer Approach for Crowd Counting and Density Estimation. - Haoyue Bai 001; Hao He 011; Zhuoxuan Peng; Tianyuan Dai; S.-H. Gary Chan (ECCV Workshops (6), 2022)

Graph-Relational Domain Adaptation. - Zihao Xu 001; Hao He 011; Guang-He Lee; Bernie Wang 001; Hao Wang 014 (ICLR, 2022)

Controlling Directions Orthogonal to a Classifier. - Yilun Xu; Hao He 011; Tianxiao Shen; Tommi S. Jaakkola (ICLR, 2022)

Domain Adaptation with Factorizable Joint Shift. - Hao He 011; Yuzhe Yang 003; Hao Wang 014 (CoRR, 2022)

1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct). - Hao Wang 014; Wanyu Lin; Hao He 011; Di Wang 015; Chengzhi Mao; Muhan Zhang (CoRR, 2022)

Contactless Oxygen Monitoring with Gated Transformer. - Hao He 011; Yuan Yuan 002; Ying-Cong Chen; Peng Cao; Dina Katabi (CoRR, 2022)

CornerRadar: RF-Based Indoor Localization Around Corners. - Shichao Yue; Hao He 011; Peng Cao; Kaiwen Zha; Masayuki Koizumi; Dina Katabi (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022)

Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks. - Jierun Chen; Shiu-Hong Kao; Hao He 011; Weipeng Zhuo; Song Wen 001; Chul-Ho Lee; S.-H. Gary Chan (CVPR, 2023)

Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning. - Hao He 011; Kaiwen Zha; Dina Katabi (ICLR, 2023)

Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation. - Zihao Xu 001; Guang-Yuan Hao; Hao He 011; Hao Wang 014 (ICLR, 2023)

Taxonomy-Structured Domain Adaptation. - Tianyi Liu; Zihao Xu 001; Hao He 011; Guang-Yuan Hao; Guang-He Lee; Hao Wang 014 (ICML, 2023)

Contactless Oxygen Monitoring with Radio Waves and Gated Transformer. - Hao He 011; Yuan Yuan 002; Ying-Cong Chen; Peng Cao; Dina Katabi (MLHC, 2023)

ReTR: Modeling Rendering Via Transformer for Generalizable Neural Surface Reconstruction. - Yixun Liang; Hao He 011; Yingcong Chen (NeurIPS, 2023)

Addressing Feature Suppression in Unsupervised Visual Representations. - Tianhong Li; Lijie Fan; Yuan Yuan 002; Hao He 011; Yonglong Tian; Rogério Feris; Piotr Indyk; Dina Katabi (WACV, 2023)

Label Name is Mantra: Unifying Point Cloud Segmentation across Heterogeneous Datasets. - Yixun Liang; Hao He 011; Shishi Xiao; Hao Lu 009; Yingcong Chen (CoRR, 2023)

Rethinking Rendering in Generalizable Neural Surface Reconstruction: A Learning-based Solution. - Yixun Liang; Hao He 011; Yingcong Chen (CoRR, 2023)

CP-NeRF: Conditionally Parameterized Neural Radiance Fields for Cross-scene Novel View Synthesis. - Hao He 011; Yixun Liang; Shishi Xiao; Jierun Chen; Yingcong Chen (Comput. Graph. Forum, 2023)

Contactless Polysomnography: What Radio Waves Tell Us about Sleep. - Hao He 011; Chao Li; Wolfgang Ganglberger; Kaileigh Gallagher; Rumen Hristov; Michail Ouroutzoglou; Haoqi Sun; Jimeng Sun 001; M. Brandon Westover; Dina Katabi (CoRR, 2024)

LucidFusion: Generating 3D Gaussians with Arbitrary Unposed Images. - Hao He 011; Yixun Liang; Luozhou Wang; Yuanhao Cai; Xinli Xu; Hao-Xiang Guo; Xiang Wen; Yingcong Chen (CoRR, 2024)

Graph-Relational Federated Learning: Enhanced Personalization and Robustness. - Wanyu Lin; Hao Lan; Hao He 011; Baochun Li (IEEE Trans. Dependable Secur. Comput., 2025)

X-LRM: X-ray Large Reconstruction Model for Extremely Sparse-View Computed Tomography Recovery in One Second. - Guofeng Zhang 025; Ruyi Zha; Hao He 011; Yixun Liang; Alan L. Yuille; Hongdong Li; Yuanhao Cai (CoRR, 2025)