5 papers
Leveraging Causal Reasoning Method for Explaining Medical Image Segmentation Models
Limai Jiang, Ruitao Xie, Bokai Yang +6
Medical image segmentation plays a vital role in clinical decision-making, enabling precise localization of lesions and guiding interventions. Despite significant advances in segme…
Automated Learning of Semantic Embedding Representations for Diffusion Models
Limai Jiang, Yunpeng Cai
Generative models capture the true distribution of data, yielding semantically rich representations. Denoising diffusion models (DDMs) exhibit superior generative capabilities, tho…
Autism Spectrum Disorder Classification with Interpretability in Children based on Structural MRI Features Extracted using Contrastive Variational Autoencoder
Ruimin Ma, Ruitao Xie, Yanlin Wang +4
Autism spectrum disorder (ASD) is a highly disabling mental disease that brings significant impairments of social interaction ability to the patients, making early screening and in…
Efficient Sampling of Temporal Networks with Preserved Causality Structure
Felix I. Stamm, Mehdi Naima, Michael T. Schaub
In this paper, we extend the classical Color Refinement algorithm for static networks to temporal (undirected and directed) networks. This enables us to design an algorithm to samp…
Accurate Explanation Model for Image Classifiers using Class Association Embedding
Ruitao Xie, Jingbang Chen, Limai Jiang +3
Image classification is a primary task in data analysis where explainable models are crucially demanded in various applications. Although amounts of methods have been proposed to o…