47 citations · 116 across the 35 of their papers we have counts for
8 papers · 1 filter
Identifying Invariant Texture Violation for Robust Deepfake Detection
Xinwei Sun, Botong Wu, Wei Chen
Existing deepfake detection methods have reported promising in-distribution results, by accessing published large-scale dataset. However, due to the non-smooth synthesis method, th…
Forecasting Irreversible Disease via Progression Learning
Botong Wu, Sijie Ren, Jing Li +3
Forecasting Parapapillary atrophy (PPA), i.e., a symptom related to most irreversible eye diseases, provides an alarm for implementing an intervention to slow down the disease prog…
Latent Causal Invariant Model
Xinwei Sun, Botong Wu, Xiangyu Zheng +4
Current supervised learning can learn spurious correlation during the data-fitting process, imposing issues regarding interpretability, out-of-distribution (OOD) generalization, an…
Learning Causal Semantic Representation for Out-of-Distribution Prediction
Chang Liu, Xinwei Sun, Jindong Wang +5
Conventional supervised learning methods, especially deep ones, are found to be sensitive to out-of-distribution (OOD) examples, largely because the learned representation mixes th…
Bilateral Asymmetry Guided Counterfactual Generating Network for Mammogram Classification
Chu-ran Wang, Jing Li, Fandong Zhang +4
Mammogram benign or malignant classification with only image-level labels is challenging due to the absence of lesion annotations. Motivated by the symmetric prior that the lesions…
Leveraging both Lesion Features and Procedural Bias in Neuroimaging: An Dual-Task Split dynamics of inverse scale space
Xinwei Sun, Wenjing Han, Lingjing Hu +2
The prediction and selection of lesion features are two important tasks in voxel-based neuroimage analysis. Existing multivariate learning models take two tasks equivalently and op…