Instance-wise Linearization of Neural Network for Model Interpretation
This work proposes an instance-wise linearization approach to reformulates the forward computation process of a neural network prediction and discusses the application of this technique in both supervise classification and unsupervised neural network learning parametric t-SNE dimension reduction.