Neural networks (NNs) and decision trees (DTs) are both popular models of machine
learning, yet coming with mutually exclusive advantages and limitations. To bring the best of …

Neural networks (NNs) and decision trees (DTs) are both popular models of machine
learning, yet coming with mutually exclusive advantages and limitations. To bring the best of …

In this paper, we strive to propose a self-interpretable framework, termed PrimitiveTree, that
incorporates deep visual primitives condensed from deep features with a conventional …

Microvascular invasion (MVI) is a critical factor for prognosis evaluation and cancer
treatment. The current diagnosis of MVI relies on pathologists to manually find out cancerous …

Convolutional neural networks have made significant strides in solving computer-vision
tasks at the expense of high computational demands. This complexity hinders efficient …

In this paper, we present Language Model as Visual Explainer LVX, a systematic approach
for interpreting the internal workings of vision models using a tree-structured linguistic …

Convolutional Neural Network (CNN), which mimics human visual perception mechanism,
has been successfully used in many computer vision areas. Some psychophysical studies …

Neural trees benefit from the high-level representation of neural networks and the
interpretability of decision trees. Therefore, the existing works on neural trees perform …