Hao Wang

Orcid: 0000-0002-7308-938X

Affiliations:
  • Rutgers University, Department of Computer Science, NJ, USA
  • Massachusetts Institute of Technology, CSAIL Cambridge, MA, USA (former)
  • Hong Kong University of Science and Technology, Department of Computer Science and Engineering, Hong Kong (former, PhD)


According to our database1, Hao Wang authored at least 62 papers between 2013 and 2024.

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Bibliography

2024
Second-Order Graph ODEs for Multi-Agent Trajectory Forecasting.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Rethinking Privacy Risks from Wireless Surveillance Camera.
ACM Trans. Sens. Networks, August, 2023

Counterfactual Collaborative Reasoning.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Self-Interpretable Time Series Prediction with Counterfactual Explanations.
Proceedings of the International Conference on Machine Learning, 2023

Robust Perception through Equivariance.
Proceedings of the International Conference on Machine Learning, 2023

Taxonomy-Structured Domain Adaptation.
Proceedings of the International Conference on Machine Learning, 2023

Domain-Indexing Variational Bayes: Interpretable Domain Index for Domain Adaptation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Landscape Learning for Neural Network Inversion.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Identifying Regional Driving Risks via Transductive Cross-City Transfer Learning Under Negative Transfer.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

FedNP: Towards Non-IID Federated Learning via Federated Neural Propagation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting.
CoRR, 2022

Visual Prompt Tuning for Test-time Domain Adaptation.
CoRR, 2022

1st ICLR International Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (PAIR^2Struct).
CoRR, 2022

Domain Adaptation with Factorizable Joint Shift.
CoRR, 2022

Extrapolative Continuous-time Bayesian Neural Network for Fast Training-free Test-time Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Earthformer: Exploring Space-Time Transformers for Earth System Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

"My nose is running." "Are you also coughing?": Building A Medical Diagnosis Agent with Interpretable Inquiry Logics.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Domain Adaptation for Time Series Forecasting via Attention Sharing.
Proceedings of the International Conference on Machine Learning, 2022

Graph-Relational Domain Adaptation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

On Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization and Beyond.
Proceedings of the Computer Vision - ECCV 2022, 2022

Social ODE: Multi-agent Trajectory Forecasting with Neural Ordinary Differential Equations.
Proceedings of the Computer Vision - ECCV 2022, 2022

Learning Interacting Dynamic Systems with Neural Ordinary Differential Equations.
Proceedings of the Dynamic Data Driven Applications Systems - 4th International Conference, 2022

Causal Transportability for Visual Recognition.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Bayesian Invariant Risk Minimization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Context Uncertainty in Contextual Bandits with Applications to Recommender Systems.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
A Survey on Bayesian Deep Learning.
ACM Comput. Surv., 2021

Zero-Shot Recommender Systems.
CoRR, 2021

Delving into Deep Imbalanced Regression.
Proceedings of the 38th International Conference on Machine Learning, 2021

STRODE: Stochastic Boundary Ordinary Differential Equation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Correcting Exposure Bias for Link Recommendation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Adversarial Attacks are Reversible with Natural Supervision.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Generative Interventions for Causal Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Authenticating On-Body IoT Devices: An Adversarial Learning Approach.
IEEE Trans. Wirel. Commun., 2020

BodyCompass: Monitoring Sleep Posture with Wireless Signals.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020

Continuously Indexed Domain Adaptation.
Proceedings of the 37th International Conference on Machine Learning, 2020

Deep Graph Random Process for Relational-Thinking-Based Speech Recognition.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees.
Proceedings of the 7th International Conference on Learning Representations, 2019

Towards Motion Invariant Authentication for On-Body IoT Devices.
Proceedings of the 2019 IEEE International Conference on Communications, 2019

Rethinking Knowledge Graph Propagation for Zero-Shot Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Recurrent Poisson Process Unit for Speech Recognition.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Extracting Multi-Person Respiration from Entangled RF Signals.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2018

2017
ZM-Net: Real-time Zero-shot Image Manipulation Network.
CoRR, 2017

Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Relational Deep Learning: A Deep Latent Variable Model for Link Prediction.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Towards Bayesian Deep Learning: A Framework and Some Existing Methods.
IEEE Trans. Knowl. Data Eng., 2016

Towards Bayesian Deep Learning: A Survey.
CoRR, 2016

Natural-Parameter Networks: A Class of Probabilistic Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Relational Collaborative Topic Regression for Recommender Systems.
IEEE Trans. Knowl. Data Eng., 2015

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Collaborative Deep Learning for Recommender Systems.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Relational Stacked Denoising Autoencoder for Tag Recommendation.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2013
Online Egocentric Models for Citation Networks.
Proceedings of the IJCAI 2013, 2013

Collaborative Topic Regression with Social Regularization for Tag Recommendation.
Proceedings of the IJCAI 2013, 2013


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