58 citations · 83 across the 10 of their papers we have counts for
4 papers · 1 filter
Interpretation of NLP models through input marginalization
Siwon Kim, Jihun Yi, Eunji Kim +1
To demystify the "black box" property of deep neural networks for natural language processing (NLP), several methods have been proposed to interpret their predictions by measuring…
Information-Theoretic Visual Explanation for Black-Box Classifiers
Jihun Yi, Eunji Kim, Siwon Kim +1
In this work, we attempt to explain the prediction of any black-box classifier from an information-theoretic perspective. For each input feature, we compare the classifier outputs…
iCaps: An Interpretable Classifier via Disentangled Capsule Networks
Dahuin Jung, Jonghyun Lee, Jihun Yi +1
We propose an interpretable Capsule Network, iCaps, for image classification. A capsule is a group of neurons nested inside each layer, and the one in the last layer is called a cl…
Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation
Jihun Yi, Sungroh Yoon
In this paper, we address the problem of image anomaly detection and segmentation. Anomaly detection involves making a binary decision as to whether an input image contains an anom…