401 citations · 900 across the 16 of their papers we have counts for
7 papers · 1 filter
Calibrating Multimodal Learning
Huan Ma. Qingyang Zhang, Changqing Zhang, Bingzhe Wu +3
Multimodal machine learning has achieved remarkable progress in a wide range of scenarios. However, the reliability of multimodal learning remains largely unexplored. In this paper…
Uncertainty-inspired Open Set Learning for Retinal Anomaly Identification
Meng Wang, Tian Lin, Lianyu Wang +21
Failure to recognize samples from the classes unseen during training is a major limitation of artificial intelligence in the real-world implementation for recognition and classific…
Trusted Multi-View Classification with Dynamic Evidential Fusion
Zongbo Han, Changqing Zhang, Huazhu Fu +1
Existing multi-view classification algorithms focus on promoting accuracy by exploiting different views, typically integrating them into common representations for follow-up tasks.…
Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions
Huan Ma, Zongbo Han, Changqing Zhang +3
Multimodal regression is a fundamental task, which integrates the information from different sources to improve the performance of follow-up applications. However, existing methods…
Trustworthy Long-Tailed Classification
Bolian Li, Zongbo Han, Haining Li +2
Classification on long-tailed distributed data is a challenging problem, which suffers from serious class-imbalance and accordingly unpromising performance especially on tail class…
Trusted Multi-View Classification
Zongbo Han, Changqing Zhang, Huazhu Fu +1
Multi-view classification (MVC) generally focuses on improving classification accuracy by using information from different views, typically integrating them into a unified comprehe…
Deep Partial Multi-View Learning
Changqing Zhang, Yajie Cui, Zongbo Han +3
Although multi-view learning has made signifificant progress over the past few decades, it is still challenging due to the diffificulty in modeling complex correlations among diffe…