Collaborative Topic Regression with Social Regularization for Tag Recommendation. - Hao Wang 014; Binyi Chen; Wu-Jun Li (IJCAI, 2013)

Online Egocentric Models for Citation Networks. - Hao Wang 014; Wu-Jun Li (IJCAI, 2013)

Relational Stacked Denoising Autoencoder for Tag Recommendation. - Hao Wang 014; Xingjian Shi; Dit-Yan Yeung (AAAI, 2015)

Collaborative Deep Learning for Recommender Systems. - Hao Wang 014; Naiyan Wang; Dit-Yan Yeung (KDD, 2015)

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting. - Xingjian Shi; Zhourong Chen; Hao Wang 014; Dit-Yan Yeung; Wai-Kin Wong; Wang-chun Woo (NIPS, 2015)

Relational Collaborative Topic Regression for Recommender Systems. - Hao Wang 014; Wu-Jun Li (IEEE Trans. Knowl. Data Eng., 2015)

Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks. - Hao Wang 014; Xingjian Shi; Dit-Yan Yeung (NIPS, 2016)

Natural-Parameter Networks: A Class of Probabilistic Neural Networks. - Hao Wang 014; Xingjian Shi; Dit-Yan Yeung (NIPS, 2016)

Towards Bayesian Deep Learning: A Survey. - Hao Wang 014; Dit-Yan Yeung (CoRR, 2016)

Towards Bayesian Deep Learning: A Framework and Some Existing Methods. - Hao Wang 014; Dit-Yan Yeung (IEEE Trans. Knowl. Data Eng., 2016)

Relational Deep Learning: A Deep Latent Variable Model for Link Prediction. - Hao Wang 014; Xingjian Shi; Dit-Yan Yeung (AAAI, 2017)

Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model. - Xingjian Shi; Zhihan Gao 001; Leonard Lausen; Hao Wang 014; Dit-Yan Yeung; Wai-Kin Wong; Wang-chun Woo (NIPS, 2017)

ZM-Net: Real-time Zero-shot Image Manipulation Network. - Hao Wang 014; Xiaodan Liang; Hao Zhang 025; Dit-Yan Yeung; Eric P. Xing (CoRR, 2017)

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)

Recurrent Poisson Process Unit for Speech Recognition. - Hengguan Huang; Hao Wang 014; Brian Mak (AAAI, 2019)

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)

Rethinking Knowledge Graph Propagation for Zero-Shot Learning. - Michael Kampffmeyer; Yinbo Chen; Xiaodan Liang; Hao Wang 014; Yujia Zhang 001; Eric P. Xing (CVPR, 2019)

Towards Motion Invariant Authentication for On-Body IoT Devices. - Yong Huang 005; Mengnian Xu; Wei Wang 050; Hao Wang 014; Tao Jiang 002; Qian Zhang 001 (ICC, 2019)

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

Training-Free Uncertainty Estimation for Neural Networks. - Lu Mi; Hao Wang 014; Yonglong Tian; Nir Shavit (CoRR, 2019)

Deep Graph Random Process for Relational-Thinking-Based Speech Recognition. - Hengguan Huang; Fuzhao Xue; Hao Wang 014; Ye Wang 007 (ICML, 2020)

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

Learning Guided Electron Microscopy with Active Acquisition. - Lu Mi; Hao Wang 014; Yaron Meirovitch; Richard Schalek; Srinivas C. Turaga; Jeff W. Lichtman; Aravinthan D. T. Samuel; Nir Shavit (MICCAI (5), 2020)

BodyCompass: Monitoring Sleep Posture with Wireless Signals. - Shichao Yue; Yuzhe Yang 003; Hao Wang 014; Hariharan Rahul; Dina Katabi (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020)

Authenticating On-Body IoT Devices: An Adversarial Learning Approach. - Yong Huang 005; Wei Wang 050; Hao Wang 014; Tao Jiang 002; Qian Zhang 001 (IEEE Trans. Wirel. Commun., 2020)

Generative Interventions for Causal Learning. - Chengzhi Mao; Augustine Cha; Amogh Gupta; Hao Wang 014; Junfeng Yang; Carl Vondrick (CVPR, 2021)

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction. - Songhua Liu; Tianwei Lin; Dongliang He; Fu Li 003; Ruifeng Deng; Xin Li 106; Errui Ding; Hao Wang 014 (ICCV, 2021)

Adversarial Attacks are Reversible with Natural Supervision. - Chengzhi Mao; Mia Chiquier; Hao Wang 014; Junfeng Yang; Carl Vondrick (ICCV, 2021)

Correcting Exposure Bias for Link Recommendation. - Shantanu Gupta; Hao Wang 014; Zachary C. Lipton; Yuyang Wang 001 (ICML, 2021)

STRODE: Stochastic Boundary Ordinary Differential Equation. - Hengguan Huang; Hongfu Liu 002; Hao Wang 014; Chang Xiao; Ye Wang 007 (ICML, 2021)

Delving into Deep Imbalanced Regression. - Yuzhe Yang 003; Kaiwen Zha; Ying-Cong Chen; Hao Wang 014; Dina Katabi (ICML, 2021)

Zero-Shot Recommender Systems. - Hao Ding 003; Yifei Ma; Anoop Deoras; Yuyang Wang 001; Hao Wang 014 (CoRR, 2021)

Revisiting Latent-Space Interpolation via a Quantitative Evaluation Framework. - Lu Mi; Tianxing He; Core Francisco Park; Hao Wang 014; Yue Wang; Nir Shavit (CoRR, 2021)

A Survey on Bayesian Deep Learning. - Hao Wang 014; Dit-Yan Yeung (ACM Comput. Surv., 2021)

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)

Context Uncertainty in Contextual Bandits with Applications to Recommender Systems. - Hao Wang 014; Yifei Ma; Hao Ding 003; Yuyang Wang 001 (AAAI, 2022)

Bayesian Invariant Risk Minimization. - Yong Lin; Hanze Dong; Hao Wang 014; Tong Zhang 001 (CVPR, 2022)

OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks. - Wanyu Lin; Hao Lan; Hao Wang 014; Baochun Li (CVPR, 2022)

Causal Transportability for Visual Recognition. - Chengzhi Mao; Kevin Xia 001; James Wang; Hao Wang 014; Junfeng Yang; Elias Bareinboim; Carl Vondrick (CVPR, 2022)

Learning Interacting Dynamic Systems with Neural Ordinary Differential Equations. - Song Wen 001; Hao Wang 014; Dimitris N. Metaxas (DDDAS, 2022)

Social ODE: Multi-agent Trajectory Forecasting with Neural Ordinary Differential Equations. - Song Wen 001; Hao Wang 014; Dimitris N. Metaxas (ECCV (22), 2022)

On Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization and Beyond. - Yuzhe Yang 003; Hao Wang 014; Dina Katabi (ECCV (20), 2022)

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

Domain Adaptation for Time Series Forecasting via Attention Sharing. - Xiaoyong Jin; Youngsuk Park; Danielle C. Maddix; Hao Wang 014; Yuyang Wang 001 (ICML, 2022)

"My nose is running." "Are you also coughing?": Building A Medical Diagnosis Agent with Interpretable Inquiry Logics. - Wenge Liu; Yi Cheng; Hao Wang 014; Jianheng Tang; Yafei Liu; Ruihui Zhao; Wenjie Li 002; Yefeng Zheng 001; Xiaodan Liang (IJCAI, 2022)

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. - Zhihan Gao 001; Xingjian Shi; Hao Wang 014; Yi Zhu 001; Yuyang Wang 001; Mu Li 003; Dit-Yan Yeung (NeurIPS, 2022)

Extrapolative Continuous-time Bayesian Neural Network for Fast Training-free Test-time Adaptation. - Hengguan Huang; Xiangming Gu; Hao Wang 014; Chang Xiao; Hongfu Liu 002; Ye Wang 007 (NeurIPS, 2022)

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

On Multi-Domain Long-Tailed Recognition, Generalization and Beyond. - Yuzhe Yang 003; Hao Wang 014; Dina Katabi (CoRR, 2022)

Unsupervised Mismatch Localization in Cross-Modal Sequential Data. - Wei Wei 037; Hengguan Huang; Xiangming Gu; Hao Wang 014; Ye Wang 007 (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)

Visual Prompt Tuning for Test-time Domain Adaptation. - Yunhe Gao; Xingjian Shi; Yi Zhu 001; Hao Wang 014; Zhiqiang Tang 001; Xiong Zhou; Mu Li 003; Dimitris N. Metaxas (CoRR, 2022)

First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting. - Xiyuan Zhang; Xiaoyong Jin; Karthick Gopalswamy; Gaurav Gupta; Youngsuk Park; Xingjian Shi; Hao Wang 014; Danielle C. Maddix; Yuyang Wang 001 (CoRR, 2022)

Unsupervised Mismatch Localization in Cross-Modal Sequential Data with Application to Mispronunciations Localization. - Wei Wei 037; Hengguan Huang; Xiangming Gu; Hao Wang 014; Ye Wang 007 (Trans. Mach. Learn. Res., 2022)

FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation. - Xueyang Wu 001; Hengguan Huang; Youlong Ding; Hao Wang 014; Ye Wang 007; Qian Xu 005 (AAAI, 2023)

Identifying Regional Driving Risks via Transductive Cross-City Transfer Learning Under Negative Transfer. - Hua Yan; Hao Wang 014; Desheng Zhang; Yu Yang 010 (CIKM, 2023)

Landscape Learning for Neural Network Inversion. - Ruoshi Liu; Chengzhi Mao; Purva Tendulkar; Hao Wang 014; Carl Vondrick (ICCV, 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)

Robust Perception through Equivariance. - Chengzhi Mao; Lingyu Zhang; Abhishek Vaibhav Joshi; Junfeng Yang; Hao Wang 014; Carl Vondrick (ICML, 2023)

Self-Interpretable Time Series Prediction with Counterfactual Explanations. - Jingquan Yan; Hao Wang 014 (ICML, 2023)

PreDiff: Precipitation Nowcasting with Latent Diffusion Models. - Zhihan Gao 001; Xingjian Shi; Boran Han; Hao Wang 014; Xiaoyong Jin; Danielle C. Maddix; Yi Zhu 001; Mu Li 003; Yuyang Wang 001 (NeurIPS, 2023)

Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting. - Marcel Kollovieh; Abdul Fatir Ansari; Michael Bohlke-Schneider; Jasper Zschiegner; Hao Wang 014; Yuyang Wang 001 (NeurIPS, 2023)

A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm. - Haizhou Shi; Hao Wang 014 (NeurIPS, 2023)

Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing. - Ziyan Wang; Hao Wang 014 (NeurIPS, 2023)

Trending Now: Modeling Trend Recommendations. - Hao Ding 003; Branislav Kveton; Yifei Ma; Youngsuk Park; Venkataramana Kini; Yupeng Gu; Ravi Divvela; Fei Wang 065; Anoop Deoras; Hao Wang 014 (RecSys, 2023)

Counterfactual Collaborative Reasoning. - Jianchao Ji; Zelong Li; Shuyuan Xu; Max Xiong; Juntao Tan; Yingqiang Ge; Hao Wang 014; Yongfeng Zhang (WSDM, 2023)

Cross-Frequency Time Series Meta-Forecasting. - Mike Van Ness; Huibin Shen; Hao Wang 014; Xiaoyong Jin; Danielle C. Maddix; Karthick Gopalswamy (CoRR, 2023)

DPFormer: Learning Differentially Private Transformer on Long-Tailed Data. - Youlong Ding; Xueyang Wu 001; Hao Wang 014; Weike Pan (CoRR, 2023)

Variational Imbalanced Regression. - Ziyan Wang; Hao Wang 014 (CoRR, 2023)

LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud. - Mengke Zhang; Tianxing He; Tianle Wang 003; Lu Mi; Fatemehsadat Mireshghallah; Binyi Chen; Hao Wang 014; Yulia Tsvetkov (CoRR, 2023)

Continuous Invariance Learning. - Yong Lin; Fan Zhou 012; Lu Tan; Lintao Ma; Jiameng Liu; Yansu He; Yuan Yuan; Yu Liu 071; James Zhang; Yujiu Yang; Hao Wang 014 (CoRR, 2023)

Pre-trained Recommender Systems: A Causal Debiasing Perspective. - Ziqian Lin; Hao Ding 003; Nghia Hoang; Branislav Kveton; Anoop Deoras; Hao Wang 014 (CoRR, 2023)

Rethinking Privacy Risks from Wireless Surveillance Camera. - Qianyi Huang; Youjing Lu; Zhicheng Luo; Hao Wang 014; Fan Wu 006; Guihai Chen; Qian Zhang 001 (ACM Trans. Sens. Networks, 2023)

Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees. - Guang-Yuan Hao; Hengguan Huang; Haotian Wang; Jie Gao; Hao Wang 014 (AAAI, 2024)

Benchmarking Large Language Models on Communicative Medical Coaching: A Dataset and a Novel System. - Hengguan Huang; Songtao Wang; Hongfu Liu 002; Hao Wang 014; Ye Wang 007 (ACL (Findings), 2024)

Variational Language Concepts for Interpreting Foundation Language Models. - Hengyi Wang; Shiwei Tan; Zhiqing Hong; Desheng Zhang; Hao Wang 014 (EMNLP (Findings), 2024)

Raidar: geneRative AI Detection viA Rewriting. - Chengzhi Mao; Carl Vondrick; Hao Wang 014; Junfeng Yang (ICLR, 2024)

Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations. - Xinyue Xu; Yi Qin; Lu Mi; Hao Wang 014; Xiaomeng Li (ICLR, 2024)

Continuous Invariance Learning. - Lin Yong; Fan Zhou 012; Lu Tan; Lintao Ma; Jianmeng Liu; Yansu He; Yuan Yuan; Yu Liu 071; James Y. Zhang; Yujiu Yang; Hao Wang 014 (ICLR, 2024)

Delving into Differentially Private Transformer. - Youlong Ding; Xueyang Wu 001; Yining Meng; Yonggang Luo; Hao Wang 014; Weike Pan (ICML, 2024)

Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models. - Hengyi Wang; Shiwei Tan; Hao Wang 014 (ICML, 2024)

LatticeGen: Hiding Generated Text in a Lattice for Privacy-Aware Large Language Model Generation on Cloud. - Mengke Zhang; Tianxing He; Tianle Wang 003; Lu Mi; Niloofar Mireshghallah; Binyi Chen; Hao Wang 014; Yulia Tsvetkov (NAACL-HLT (Findings), 2024)

BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models. - Yibin Wang 005; Haizhou Shi; Ligong Han; Dimitris N. Metaxas; Hao Wang 014 (NeurIPS, 2024)

Natural Counterfactuals With Necessary Backtracking. - Guang-Yuan Hao; Jiji Zhang; Biwei Huang; Hao Wang 014; Kun Zhang 001 (NeurIPS, 2024)

Second-Order Graph ODEs for Multi-Agent Trajectory Forecasting. - Song Wen 001; Hao Wang 014; Di Liu 003; Qilong Zhangli; Dimitris N. Metaxas (WACV, 2024)

Pre-trained Recommender Systems: A Causal Debiasing Perspective. - Ziqian Lin; Hao Ding 003; Trong Nghia Hoang; Branislav Kveton; Anoop Deoras; Hao Wang 014 (WSDM, 2024)

Benchmarking Large Language Models on Communicative Medical Coaching: a Novel System and Dataset. - Hengguan Huang; Songtao Wang; Hongfu Liu 002; Hao Wang 014; Ye Wang 007 (CoRR, 2024)

Continual Learning of Large Language Models: A Comprehensive Survey. - Haizhou Shi; Zihao Xu 001; Hengyi Wang; Weiyi Qin; Wenyuan Wang; Yibin Wang 005; Hao Wang 014 (CoRR, 2024)

Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion Models. - Xinxi Zhang; Song Wen 001; Ligong Han; Felix Juefei-Xu; Akash Srivastava; Junzhou Huang; Hao Wang 014; Molei Tao; Dimitris N. Metaxas (CoRR, 2024)

Verbalized Probabilistic Graphical Modeling with Large Language Models. - Hengguan Huang; Xing Shen 001; Songtao Wang; Dianbo Liu; Hao Wang 014 (CoRR, 2024)

Towards Domain Adaptive Neural Contextual Bandits. - Ziyan Wang; Hao Wang 014 (CoRR, 2024)

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models. - Haizhou Shi; Yibin Wang 005; Ligong Han; Huan Zhang; Hao Wang 014 (CoRR, 2024)

Chronos: Learning the Language of Time Series. - Abdul Fatir Ansari; Lorenzo Stella; Ali Caner Türkmen; Xiyuan Zhang; Pedro Mercado; Huibin Shen; Oleksandr Shchur; Syama Sundar Rangapuram; Sebastian Pineda-Arango; Shubham Kapoor; Jasper Zschiegner; Danielle C. Maddix; et al. (Trans. Mach. Learn. Res., 2024)

Implicit In-context Learning. - Zhuowei Li 002; Zihao Xu 001; Ligong Han; Yunhe Gao; Song Wen 001; Di Liu 003; Hao Wang 014; Dimitris N. Metaxas (ICLR, 2025)

On Calibration of LLM-based Guard Models for Reliable Content Moderation. - Hongfu Liu 002; Hengguan Huang; Xiangming Gu; Hao Wang 014; Ye Wang 007 (ICLR, 2025)

GenVP: Generating Visual Puzzles with Contrastive Hierarchical VAEs. - Kalliopi Basioti; Pritish Sahu; Tony Qingze Liu; Zihao Xu 001; Hao Wang 014; Vladimir Pavlovic 001 (ICLR, 2025)

Towards Domain Adaptive Neural Contextual Bandits. - Ziyan Wang; Xiaoming Huo; Hao Wang 014 (ICLR, 2025)

Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models. - Hengyi Wang; Haizhou Shi; Shiwei Tan; Weiyi Qin; Wenyuan Wang; Tunyu Zhang; Akshay Nambi 001; Tanuja Ganu; Hao Wang 014 (NAACL (Long Papers), 2025)

SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models. - Xinxi Zhang; Song Wen 001; Ligong Han; Felix Juefei-Xu; Akash Srivastava; Junzhou Huang; Vladimir Pavlovic 001; Hao Wang 014; Molei Tao; Dimitris N. Metaxas (WACV, 2025)

The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models via Visual Information Steering. - Zhuowei Li 002; Haizhou Shi; Yunhe Gao; Di Liu 003; Zhenting Wang; Yuxiao Chen 002; Ting Liu 005; Long Zhao 003; Hao Wang 014; Dimitris N. Metaxas (CoRR, 2025)

fMoE: Fine-Grained Expert Offloading for Large Mixture-of-Experts Serving. - Hanfei Yu; Xingqi Cui; Hong Zhang 025; Hao Wang 014; Hao Wang 022 (CoRR, 2025)

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation. - Ziyan Wang; Sizhe Wei; Xiaoming Huo; Hao Wang 014 (CoRR, 2025)

Effectively Steer LLM To Follow Preference via Building Confident Directions. - Bingqing Song; Boran Han; Shuai Zhang 007; Hao Wang 014; Haoyang Fang; Bonan Min; Yuyang Wang 001; Mingyi Hong 001 (CoRR, 2025)

Token-Level Uncertainty Estimation for Large Language Model Reasoning. - Tunyu Zhang; Haizhou Shi; Yibin Wang 005; Hengyi Wang; Xiaoxiao He; Zhuowei Li 002; Haoxian Chen 005; Ligong Han; Kai Xu; Huan Zhang; Dimitris N. Metaxas; Hao Wang 014 (CoRR, 2025)

Lossless Token Sequence Compression via Meta-Tokens. - John Harvill; Ziwei Fan 001; Hao Wang 014; Yizhou Sun; Hao Ding 003; Luke Huan; Anoop Deoras (CoRR, 2025)

Visual Sparse Steering: Improving Zero-shot Image Classification with Sparsity Guided Steering Vectors. - Gerasimos Chatzoudis; Zhuowei Li 002; Gemma E. Moran; Hao Wang 014; Dimitris N. Metaxas (CoRR, 2025)

Does Multimodality Lead to Better Time Series Forecasting? - Xiyuan Zhang; Boran Han; Haoyang Fang; Abdul Fatir Ansari; Shuai Zhang 007; Danielle C. Maddix; Cuixiong Hu; Andrew Gordon Wilson; Michael W. Mahoney; Hao Wang 014; Yan Liu; Huzefa Rangwala; et al. (CoRR, 2025)

Graph-Guided Dual-Level Augmentation for 3D Scene Segmentation. - Hongbin Lin; Yifan Jiang; Juangui Xu; Jesse Jiaxi Xu; Yi Lu; Zhengyu Hu; Ying-Cong Chen; Hao Wang 014 (CoRR, 2025)