… Deep neural networks and decision trees operate … adaptive neural trees (ANTs) that
incorporates representation learning into edges, routing functions and leaf nodes of a decision tree, …

… An adaptive neural decision tree is investigated … adaptive neural decision tree (ANT) based
emotion recognition method is explored by embedding neural networks into the decision tree …

… in hybrid neural trees with different MLPs, but there is not any neural tree with expert nodes.
By applying some if–then rules, these nodes can be extended to select an eligible neural …

… tree with simple nodes may become very large. They proposed a new class of DTs where …
In this paper, a new neural-tree model, called adaptive high order neural tree (AHNT), is …

… trees and the learning paradigm of neural networks. We call our model an online adaptive
decision tree (OADT), which can learn in the online mode and can exhibit adaptive behavior (…

… Neural networks (NNs) and decision trees (DTs) are both popular models of machine …
In this survey, these approaches are organized in a school which we term as neural trees (NTs). …

… Accordingly, we include here a brief survey of neural network trees. The … a neuron. An
interesting finding of this work was that some their algorithms tended to produce neural trees in …

… Neural trees are also very convenient for … the neural tree representation scheme. Section
4 describes the evolutionary algorithms for adapting the structures and weights of neural trees. …

… constructing the adaptive Tree-CNN block. The learned Tree-CNN network structure can
assist in differentiating easily confused classes. As far as we know, it is the first adaptive CNN …

… tree like plausible biological properties, BNeuralT is a single neuron neural tree model with
its internal sub-trees … BNeuralT algorithm produces an ad hoc neural tree which is trained …