2 papers
cs.CV2024
EQ-CBM: A Probabilistic Concept Bottleneck with Energy-based Models and Quantized Vectors
Sangwon Kim, Dasom Ahn, Byoung Chul Ko +2
The demand for reliable AI systems has intensified the need for interpretable deep neural networks. Concept bottleneck models (CBMs) have gained attention as an effective approach…
cs.AI2020
Interpretation and Simplification of Deep Forest
Sangwon Kim, Mira Jeong, Byoung Chul Ko
This paper proposes a new method for interpreting and simplifying a black box model of a deep random forest (RF) using a proposed rule elimination. In deep RF, a large number of de…