3 papers
cs.LG2021
Self-learn to Explain Siamese Networks Robustly
Chao Chen, Yifan Shen, Guixiang Ma +4
Learning to compare two objects are essential in applications, such as digital forensics, face recognition, and brain network analysis, especially when labeled data is scarce and i…
cs.SI2020
Rigorous Explanation of Inference on Probabilistic Graphical Models
Yifei Liu, Chao Chen, Xi Zhang +1
Probabilistic graphical models, such as Markov random fields (MRF), exploit dependencies among random variables to model a rich family of joint probability distributions. Sophistic…
cs.SI2019
Scalable Explanation of Inferences on Large Graphs
Chao Chen, Yifei Liu, Xi Zhang +1
Probabilistic inferences distill knowledge from graphs to aid human make important decisions. Due to the inherent uncertainty in the model and the complexity of the knowledge, it i…