In recent years, many accurate decision support systems have been constructed as black
boxes, that is as systems that hide their internal logic to the user. This lack of explanation …

Introduction: The radiological reading room is undergoing a paradigm shift to a symbiosis of
computer science and radiology using artificial intelligence integrated with machine and …

Recent image generation models such as Stable Diffusion have exhibited an impressive
ability to generate fairly realistic images starting from a simple text prompt. Could such …

Deep learning has recently seen rapid development and received significant attention due
to its state-of-the-art performance on previously-thought hard problems. However, because …

We propose a technique for producing'visual explanations' for decisions from a large class
of Convolutional Neural Network (CNN)-based models, making them more transparent. Our …

We propose a technique for producing 'visual explanations' for decisions from a large class
of Convolutional Neural Network (CNN)-based models, making them more transparent and …

We consider image transformation problems, where an input image is transformed into an
output image. Recent methods for such problems typically train feed-forward convolutional …

We propose a technique for making Convolutional Neural Network (CNN)-based models
more transparent by visualizing input regions that are'important'for predictions--or visual …

While neural networks have been successfully applied to many natural language processing
tasks, they come at the cost of interpretability. In this paper, we propose a general …

The fast expanding of social media fuels the spreading of misinformation which disrupts
people's normal lives. It is urgent to achieve goals of misinformation identification and early …