2 code implementations • 30 Dec 2021 • Erico Tjoa, Hong Jing Khok, Tushar Chouhan, Guan Cuntai
This paper quantifies the quality of heatmap-based eXplainable AI (XAI) methods w. r. t image classification problem.
1 code implementation • 30 Dec 2021 • Erico Tjoa, Guan Cuntai
This paper proposes a way to circumvent the issues through the bottom-up design of neural networks with detailed interpretability, where each neuron or layer has its own meaning and utility that corresponds to humanly understandable concept.
2 code implementations • 30 Dec 2021 • Erico Tjoa, Guan Cuntai
This paper proposes two bottom-up interpretable neural network (NN) constructions for universal approximation, namely Triangularly-constructed NN (TNN) and Semi-Quantized Activation NN (SQANN).
no code implementations • 5 Feb 2021 • Erico Tjoa, Guan Cuntai
Ongoing efforts to understand deep neural networks (DNN) have provided many insights, but DNNs remain incompletely understood.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI) +1
2 code implementations • 5 Sep 2020 • Erico Tjoa, Guan Cuntai
The practical application of deep neural networks are still limited by their lack of transparency.