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Autor:
Hayashi, Naoki, Sawada, Yoshihide
Concept Bottleneck Model (CBM) is a methods for explaining neural networks. In CBM, concepts which correspond to reasons of outputs are inserted in the last intermediate layer as observed values. It is expected that we can interpret the relationship
Externí odkaz:
http://arxiv.org/abs/2403.09206
Autor:
Hayashi, Naoki, Sawada, Yoshihide
Concept bottleneck model (CBM) is a ubiquitous method that can interpret neural networks using concepts. In CBM, concepts are inserted between the output layer and the last intermediate layer as observable values. This helps in understanding the reas
Externí odkaz:
http://arxiv.org/abs/2303.09154
Autor:
Pandey, Gita Sadaula, Manandhar, Prajwol, Shrestha, Bijaya Kumar, Sadaula, Amir, Hayashi, Naoki, Abdelbaset, Abdelbaset Eweda, Silwal, Pradeepa, Tsubota, Toshio, Kwak, Mackenzie L., Nonaka, Nariaki, Nakao, Ryo
Publikováno v:
In Acta Tropica October 2024 258