3 citations · 5 across the 5 of their papers we have counts for
5 papers
Falcon-X: A Time Series Foundation Model for Heterogeneous Multivariate Modeling
Yiding Liu, Yifan Hu, Hongjie Xia +5
Time series foundation models (TSFMs) are transforming the forecasting paradigm through large-scale cross-domain pretraining. However, most existing TSFMs remain univariate, and re…
ProtoSolo: Interpretable Image Classification via Single-Prototype Activation
Yitao Peng, Lianghua He, Hongzhou Chen
Although interpretable prototype networks have improved the transparency of deep learning image classification, the need for multiple prototypes in collaborative decision-making in…
AFiRe: Anatomy-Driven Self-Supervised Learning for Fine-Grained Representation in Radiographic Images
Yihang Liu, Lianghua He, Ying Wen +2
Current self-supervised methods, such as contrastive learning, predominantly focus on global discrimination, neglecting the critical fine-grained anatomical details required for ac…
Visual Neural Decoding via Improved Visual-EEG Semantic Consistency
Hongzhou Chen, Lianghua He, Yihang Liu +3
Visual neural decoding aims to extract and interpret original visual experiences directly from human brain activity. Recent studies have demonstrated the feasibility of decoding vi…
Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image Captioning
Longzhen Yang, Yihang Liu, Yitao Peng +1
Accuracy and Diversity are two essential metrizable manifestations in generating natural and semantically correct captions. Many efforts have been made to enhance one of them with…