5 citations · 11 across the 4 of their papers we have counts for
4 papers
Explaining How a Neural Network Play the Go Game and Let People Learn
Huilin Zhou, Huijie Tang, Mingjie Li +3
The AI model has surpassed human players in the game of Go, and it is widely believed that the AI model has encoded new knowledge about the Go game beyond human players. In this wa…
Explaining Generalization Power of a DNN Using Interactive Concepts
Huilin Zhou, Hao Zhang, Huiqi Deng +4
This paper explains the generalization power of a deep neural network (DNN) from the perspective of interactions. Although there is no universally accepted definition of the concep…
Building Interpretable Interaction Trees for Deep NLP Models
Die Zhang, Huilin Zhou, Hao Zhang +6
This paper proposes a method to disentangle and quantify interactions among words that are encoded inside a DNN for natural language processing. We construct a tree to encode salie…
Interpretable CNNs for Object Classification
Quanshi Zhang, Xin Wang, Ying Nian Wu +2
This paper proposes a generic method to learn interpretable convolutional filters in a deep convolutional neural network (CNN) for object classification, where each interpretable f…