Wenbo Hu

Orcid: 0000-0002-0639-2012

Affiliations:
  • School of Computer Science and Information, Hefei University of Technology, Hefei, China
  • Tsinghua University, State Key Laboratory of Intelligent Technology and Systems, TNList, Beijing, China (former)
  • Tsinghua University, Department of Computer Science and Technology, Beijing, China (former)


According to our database1, Wenbo Hu authored at least 24 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Iterative Adversarial Attack on Image-Guided Story Ending Generation.
IEEE Trans. Multim., 2024

AtomTool: Empowering Large Language Models with Tool Utilization Skills.
Proceedings of the Pattern Recognition and Computer Vision - 7th Chinese Conference, 2024

2023
Deep Ensembles Meets Quantile Regression: Uncertainty-aware Imputation for Time Series.
CoRR, 2023

Investigating Uncertainty Calibration of Aligned Language Models under the Multiple-Choice Setting.
CoRR, 2023

Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning.
CoRR, 2023

Client: Cross-variable Linear Integrated Enhanced Transformer for Multivariate Long-Term Time Series Forecasting.
CoRR, 2023

Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation.
CoRR, 2023

Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

How to Use Language Expert to Assist Inference for Visual Commonsense Reasoning.
Proceedings of the IEEE International Conference on Data Mining, 2023

2022
StackVAE-G: An efficient and interpretable model for time series anomaly detection.
AI Open, January, 2022

TgDLF2.0: Theory-guided deep-learning for electrical load forecasting via Transformer and transfer learning.
CoRR, 2022

2021
KO-PDE: Kernel Optimized Discovery of Partial Differential Equations with Varying Coefficients.
CoRR, 2021

Stacking VAE with Graph Neural Networks for Effective and Interpretable Time Series Anomaly Detection.
CoRR, 2021

Accurate and Reliable Forecasting using Stochastic Differential Equations.
CoRR, 2021

Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020
Series Saliency: Temporal Interpretation for Multivariate Time Series Forecasting.
CoRR, 2020

Dynamic Window-level Granger Causality of Multi-channel Time Series.
CoRR, 2020

Calibrated Reliable Regression using Maximum Mean Discrepancy.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2017
Fast sampling methods for Bayesian max-margin models.
Expert Syst. Appl., 2017

SAM: Semantic Attribute Modulated Language Modeling.
CoRR, 2017

Semi-supervised Max-margin Topic Model with Manifold Posterior Regularization.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2015
Stochastic Subgradient MCMC Methods.
CoRR, 2015

2014
Big Learning with Bayesian Methods.
CoRR, 2014

2012
Neural-network-based cooperative adaptive identification of nonlinear systems.
Proceedings of the 12th International Conference on Control Automation Robotics & Vision, 2012


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