Hao Wang

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 71

Top Topics

Diffusion Models

Tag Recommendation

Domain Adaptation

Top Venues

Publications

Chengzhi Mao, Carl Vondrick, Hao Wang, Junfeng Yang
Raidar: geneRative AI Detection viA Rewriting. ICLR (2024)
Guang-Yuan Hao, Hengguan Huang, Haotian Wang, Jie Gao, Hao Wang
Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees. AAAI (2024)
Song Wen, Hao Wang, Di Liu, Qilong Zhangli, Dimitris N. Metaxas
Second-Order Graph ODEs for Multi-Agent Trajectory Forecasting. WACV (2024)
Zhuowei Li, Zihao Xu, Ligong Han, Yunhe Gao, Song Wen, Di Liu, Hao Wang, Dimitris N. Metaxas
Implicit In-context Learning. CoRR (2024)
Xinxi Zhang, Song Wen, Ligong Han, Felix Juefei-Xu, Akash Srivastava, Junzhou Huang, Hao Wang, Molei Tao, Dimitris N. Metaxas
Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models. CoRR (2024)
Hengguan Huang, Songtao Wang, Hongfu Liu, Hao Wang, Ye Wang
Benchmarking Large Language Models on Communicative Medical Coaching: A Dataset and a Novel System. ACL (Findings) (2024)
Ziqian Lin, Hao Ding, Trong Nghia Hoang, Branislav Kveton, Anoop Deoras, Hao Wang
Pre-trained Recommender Systems: A Causal Debiasing Perspective. WSDM (2024)
Yibin Wang, Haizhou Shi, Ligong Han, Dimitris N. Metaxas, Hao Wang
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models. CoRR (2024)
Youlong Ding, Xueyang Wu, Yining Meng, Yonggang Luo, Hao Wang, Weike Pan
Delving into Differentially Private Transformer. CoRR (2024)
Qianyi Huang, Youjing Lu, Zhicheng Luo, Hao Wang, Fan Wu, Guihai Chen, Qian Zhang
Rethinking Privacy Risks from Wireless Surveillance Camera. ACM Trans. Sens. Networks 19 (3) (2023)
Chengzhi Mao, Lingyu Zhang, Abhishek Vaibhav Joshi, Junfeng Yang, Hao Wang, Carl Vondrick
Robust Perception through Equivariance. ICML (2023)
Zihao Xu, Guang-Yuan Hao, Hao He, Hao Wang
Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation. ICLR (2023)
Jingquan Yan, Hao Wang
Self-Interpretable Time Series Prediction with Counterfactual Explanations. ICML (2023)
Hua Yan, Hao Wang, Desheng Zhang, Yu Yang
Identifying Regional Driving Risks via Transductive Cross-City Transfer Learning Under Negative Transfer. CIKM (2023)
Tianyi Liu, Zihao Xu, Hao He, Guang-Yuan Hao, Guang-He Lee, Hao Wang
Taxonomy-Structured Domain Adaptation. ICML (2023)
Tianyi Liu, Zihao Xu, Hao He, Guang-Yuan Hao, Guang-He Lee, Hao Wang
Taxonomy-Structured Domain Adaptation. CoRR (2023)
Xueyang Wu, Hengguan Huang, Youlong Ding, Hao Wang, Ye Wang, Qian Xu
FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation. AAAI (2023)
Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting. NeurIPS (2023)
Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting. CoRR (2023)
Yong Lin, Hanze Dong, Hao Wang, Tong Zhang
Bayesian Invariant Risk Minimization. CVPR (2022)
Wanyu Lin, Hao Lan, Hao Wang, Baochun Li
OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks. CVPR (2022)
Lu Mi, Hao Wang, Yonglong Tian, Hao He, Nir Shavit
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate. AAAI (2022)
Song Wen, Hao Wang, Dimitris N. Metaxas
Social ODE: Multi-agent Trajectory Forecasting with Neural Ordinary Differential Equations. ECCV (22) (2022)
Yuzhe Yang, Hao Wang, Dina Katabi
On Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization and Beyond. ECCV (20) (2022)
Wenge Liu, Yi Cheng, Hao Wang, Jianheng Tang, Yafei Liu, Ruihui Zhao, Wenjie Li, Yefeng Zheng, Xiaodan Liang
"My nose is running." "Are you also coughing?": Building A Medical Diagnosis Agent with Interpretable Inquiry Logics. IJCAI (2022)
Chengzhi Mao, Kevin Xia, James Wang, Hao Wang, Junfeng Yang, Elias Bareinboim, Carl Vondrick
Causal Transportability for Visual Recognition. CVPR (2022)
Hao Wang, Yifei Ma, Hao Ding, Yuyang Wang
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems. AAAI (2022)
Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. NeurIPS (2022)
Chengzhi Mao, Kevin Xia, James Wang, Hao Wang, Junfeng Yang, Elias Bareinboim, Carl Vondrick
Causal Transportability for Visual Recognition. CoRR (2022)
Zihao Xu, Hao He, Guang-He Lee, Bernie Wang, Hao Wang
Graph-Relational Domain Adaptation. ICLR (2022)
Xiaoyong Jin, Youngsuk Park, Danielle C. Maddix, Hao Wang, Yuyang Wang
Domain Adaptation for Time Series Forecasting via Attention Sharing. ICML (2022)
Wenge Liu, Yi Cheng, Hao Wang, Jianheng Tang, Yafei Liu, Ruihui Zhao, Wenjie Li, Yefeng Zheng, Xiaodan Liang
"My nose is running.""Are you also coughing?": Building A Medical Diagnosis Agent with Interpretable Inquiry Logics. CoRR (2022)
Song Wen, Hao Wang, Dimitris Metaxas
Learning Interacting Dynamic Systems with Neural Ordinary Differential Equations. DDDAS (2022)
Hengguan Huang, Xiangming Gu, Hao Wang, Chang Xiao, Hongfu Liu, Ye Wang
Extrapolative Continuous-time Bayesian Neural Network for Fast Training-free Test-time Adaptation. NeurIPS (2022)
Ruoshi Liu, Chengzhi Mao, Purva Tendulkar, Hao Wang, Carl Vondrick
Landscape Learning for Neural Network Inversion. CoRR (2022)
Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang
STRODE: Stochastic Boundary Ordinary Differential Equation. CoRR (2021)
Chengzhi Mao, Augustine Cha, Amogh Gupta, Hao Wang, Junfeng Yang, Carl Vondrick
Generative Interventions for Causal Learning. CVPR (2021)
Chengzhi Mao, Mia Chiquier, Hao Wang, Junfeng Yang, Carl Vondrick
Adversarial Attacks are Reversible with Natural Supervision. ICCV (2021)
Shantanu Gupta, Hao Wang, Zachary C. Lipton, Yuyang Wang
Correcting Exposure Bias for Link Recommendation. CoRR (2021)
Chengzhi Mao, Mia Chiquier, Hao Wang, Junfeng Yang, Carl Vondrick
Adversarial Attacks are Reversible with Natural Supervision. CoRR (2021)
Shantanu Gupta, Hao Wang, Zachary Lipton, Yuyang Wang
Correcting Exposure Bias for Link Recommendation. ICML (2021)
Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang
STRODE: Stochastic Boundary Ordinary Differential Equation. ICML (2021)
Songhua Liu, Tianwei Lin, Dongliang He, Fu Li, Ruifeng Deng, Xin Li, Errui Ding, Hao Wang
Paint Transformer: Feed Forward Neural Painting with Stroke Prediction. ICCV (2021)
Yuzhe Yang, Kaiwen Zha, Ying-Cong Chen, Hao Wang, Dina Katabi
Delving into Deep Imbalanced Regression. CoRR (2021)
Yuzhe Yang, Kaiwen Zha, Ying-Cong Chen, Hao Wang, Dina Katabi
Delving into Deep Imbalanced Regression. ICML (2021)
Hao Ding, Yifei Ma, Anoop Deoras, Yuyang Wang, Hao Wang
Zero-Shot Recommender Systems. CoRR (2021)
Hengguan Huang, Fuzhao Xue, Hao Wang, Ye Wang
Deep Graph Random Process for Relational-Thinking-Based Speech Recognition. CoRR (2020)
Hao Wang, Hao He, Dina Katabi
Continuously Indexed Domain Adaptation. ICML (2020)
Chengzhi Mao, Amogh Gupta, Augustine Cha, Hao Wang, Junfeng Yang, Carl Vondrick
Generative Interventions for Causal Learning. CoRR (2020)
Hengguan Huang, Fuzhao Xue, Hao Wang, Ye Wang
Deep Graph Random Process for Relational-Thinking-Based Speech Recognition. ICML (2020)
Hao Wang, Hao He, Dina Katabi
Continuously Indexed Domain Adaptation. CoRR (2020)
Shichao Yue, Yuzhe Yang, Hao Wang, Hariharan Rahul, Dina Katabi
BodyCompass: Monitoring Sleep Posture with Wireless Signals. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4 (2) (2020)
Yong Huang, Wei Wang, Hao Wang, Tao Jiang, Qian Zhang
Authenticating On-Body IoT Devices: An Adversarial Learning Approach. IEEE Trans. Wirel. Commun. 19 (8) (2020)
Hao Wang, Chengzhi Mao, Hao He, Mingmin Zhao, Tommi S. Jaakkola, Dina Katabi
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling. CoRR (2019)
Hao He, Hao Wang, Guang-He Lee, Yonglong Tian
ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees. ICLR (Poster) (2019)
Hao Wang, Chengzhi Mao, Hao He, Mingmin Zhao, Tommi S. Jaakkola, Dina Katabi
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling. AAAI (2019)
Hengguan Huang, Hao Wang, Brian Mak
Recurrent Poisson Process Unit for Speech Recognition. AAAI (2019)
Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang, Hao Wang, Yujia Zhang, Eric P. Xing
Rethinking Knowledge Graph Propagation for Zero-Shot Learning. CVPR (2019)
Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang, Hao Wang, Yujia Zhang, Eric P. Xing
Rethinking Knowledge Graph Propagation for Zero-Shot Learning. CoRR (2018)
Shichao Yue, Hao He, Hao Wang, Hariharan Rahul, Dina Katabi
Extracting Multi-Person Respiration from Entangled RF Signals. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2 (2) (2018)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Relational Deep Learning: A Deep Latent Variable Model for Link Prediction. AAAI (2017)
Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model. NIPS (2017)
Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model. CoRR (2017)
Hao Wang, Xiaodan Liang, Hao Zhang, Dit-Yan Yeung, Eric P. Xing
ZM-Net: Real-time Zero-shot Image Manipulation Network. CoRR (2017)
Hao Wang, Dit-Yan Yeung
Towards Bayesian Deep Learning: A Framework and Some Existing Methods. IEEE Trans. Knowl. Data Eng. 28 (12) (2016)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks. CoRR (2016)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Natural-Parameter Networks: A Class of Probabilistic Neural Networks. CoRR (2016)
Hao Wang, Dit-Yan Yeung
Towards Bayesian Deep Learning: A Survey. CoRR (2016)
Hao Wang, Dit-Yan Yeung
Towards Bayesian Deep Learning: A Framework and Some Existing Methods. CoRR (2016)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Natural-Parameter Networks: A Class of Probabilistic Neural Networks. NIPS (2016)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks. NIPS (2016)
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting. NIPS (2015)
Hao Wang, Xingjian Shi, Dit-Yan Yeung
Relational Stacked Denoising Autoencoder for Tag Recommendation. AAAI (2015)
Hao Wang, Naiyan Wang, Dit-Yan Yeung
Collaborative Deep Learning for Recommender Systems. KDD (2015)
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, Wang-chun Woo
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting. CoRR (2015)
Hao Wang, Wu-Jun Li
Relational Collaborative Topic Regression for Recommender Systems. IEEE Trans. Knowl. Data Eng. 27 (5) (2015)
Hao Wang, Naiyan Wang, Dit-Yan Yeung
Collaborative Deep Learning for Recommender Systems. CoRR (2014)
Hao Wang, Wu-Jun Li
Online Egocentric Models for Citation Networks. IJCAI (2013)
Hao Wang, Binyi Chen, Wu-Jun Li
Collaborative Topic Regression with Social Regularization for Tag Recommendation. IJCAI (2013)