1 code implementation • 1 Mar 2024 • Zenan Li, Zehua Liu, Yuan YAO, Jingwei Xu, Taolue Chen, Xiaoxing Ma, Jian Lü
In this paper, we present a new framework for learning with logical constraints.
1 code implementation • 1 Mar 2024 • Zenan Li, Yuan YAO, Taolue Chen, Jingwei Xu, Chun Cao, Xiaoxing Ma, Jian Lü
Neuro-symbolic learning generally consists of two separated worlds, i. e., neural network training and symbolic constraint solving, whose success hinges on symbol grounding, a fundamental problem in AI.
no code implementations • 6 Oct 2019 • Zenan Li, Xiaoxing Ma, Chang Xu, Jingwei Xu, Chun Cao, Jian Lü
Trained DNN models are increasingly adopted as integral parts of software systems, but they often perform deficiently in the field.
1 code implementation • 6 Jun 2019 • Zenan Li, Xiaoxing Ma, Chang Xu, Chun Cao, Jingwei Xu, Jian Lü
With the increasing adoption of Deep Neural Network (DNN) models as integral parts of software systems, efficient operational testing of DNNs is much in demand to ensure these models' actual performance in field conditions.