Wenbo Hu's Homepage – News!

[2024] [2023] [Earlier]

2024

[service] I am serving as an area chair for ICLR 2025. (Aug/24)
[Paper] Our recent paper titled Accurate and Reliable Forecasting using Stochastic Differential Equations is accepted to ACM TKDD. (Aug/24)
[Paper] Our recent paper titled Spatial and Temporal Implicit Semantic Relational Inference for Cross-Modal Retrieval is accepted to IEEE TCSVT. (June/24)
[Paper] Our recent paper titled A dilated convolution based method with time series fine tuning for data-driven crack length estimation is accepted to Fatigue & Fracture of Engineering Materials & Structures. (Mar/24)
[Paper] Our recent paper titled Investigating Uncertainty Calibration of Aligned Language Models under the Multiple-Choice Setting is accepted to ICLR 2024 Workshop ME-FoMo. (Mar/24)
[ML-Reading] Call for participants of the machine learning reading groups for the spring of 2024! 欢迎加入2024年第二届斛兵机器学习读书会！See here. (Jan/24)

2023

[Paper] Our recent paper titled Iterative Adversarial Attack on Image-guided Story Ending Generation is accepted to IEEE Transactions on Multimedia. (Dec/23)
[preprint] Our recent preprint Deep Ensembles Meets Quantile Regression: Uncertainty-aware Imputation for Time Series is online. (Dec/23)
[preprint] Our recent preprint Investigating Uncertainty Calibration of Aligned Language Models under the Multiple-Choice Setting is online. (Oct/23)
[service] I am serving as an area chair for ICLR 2024. (Sep/23)
[preprint] Our recent preprint Exploring Transferability of Multimodal Adversarial Samples for Vision-Language Pre-training Models with Contrastive Learning is online. (August/23)
[ML-Reading] The first machine learning reading group has finished. See this news in Chinese. (July/23)
[preprint] Our recent preprint Client: Cross-variable Linear Integrated Enhanced Transformer for Multivariate Long-Term Time Series Forecasting is online and accepted to KDD 2023 Workshop on Mining and Learning from Time Series (KDD’23-MiLeTS). (June/23)
[preprint] Our recent preprint Iterative Adversarial Attack on Image-guided Story Ending Generation is online. (May/23)
[Paper] Our recent paper “Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations” has been accepted to KDD 2023. (May/23)
[Paper] Our recent paper “An adaptive deep-learning load forecasting framework by integrating Transformer anddomain knowledge” has been accepted to Advances in Applied Energy (IF: 11.45). (May/23)
[preprint] Our recent preprint Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation is online. (March/23)
[service] I start to serve as an Editorial Board Member of ACM Transactions on Probabilistic Machine Learning (TOPML). (March/23)

Earlier

[Paper] Our recent paper titled Kernel Optimized Discovery of Partial Differential Equations with Varying Coefficients is accepted to NeurIPS 2022 Workshop AI4Science. (Oct/22)
[Paper] Our recent paper on time series anomaly detection is accepted to AI Open. (July/22)
[Paper] Our recent paper on the electrical load forecast is accepted to ICAE 2022! (June/22)
[Software] We opensource RealSeries, a comprehensive out-of-the-box Python toolkit for various tasks, including Anomaly Detection, Granger causality and Forecast and Imputation, of dealing with Time Series Datasets. (Nov/21)
[Paper] Our paper on Saliency for time series forecasting is accepted to IJCAI 2021. (April/21)
[Paper] Our paper on Calibrated Reliable Regression using Maximum Mean Discrepancy is accepted to NeurIPS 2020. (Sep/20)