Mammo-SAE : Interpreting Breast Cancer Concept Learning with Sparse Autoencoders

Bibliographic Details
Title:	Mammo-SAE : Interpreting Breast Cancer Concept Learning with Sparse Autoencoders
Authors:	Nakka, Krishna Kanth^Aff16
Contributors:	Goos, Gerhard, Founding Editor^Aff1, Hartmanis, Juris, Founding Editor^Aff2, Bertino, Elisa, Series Editor^Aff3, Gao, Wen, Series Editor^Aff4, Steffen, Bernhard, Series Editor^Aff5, Yung, Moti, Series Editor^Aff6, Zhang, Tianyu, editor^Aff7, Saldanha, Oliver Lester, editor^Aff8, Han, Luyi, editor^Aff9, Rasoolzadeh, Nika, editor^Aff10, Garrucho Moras, Lidia, editor^Aff11, van Dijk, Jarek, editor^Aff12, Tan, Tao, editor^Aff13, Kather, Jakob Nikolas, editor^Aff14, Mann, Ritse, editor^Aff15
Source:	Artificial Intelligence and Imaging for Diagnostic and Treatment Challenges in Breast Care : Second Deep Breast Workshop, Deep-Breath 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings. 16142:11-20
Database:	Springer Nature eBooks

Description
ISBN:	9783032055583 9783032055590
DOI:	10.1007/978-3-032-05559-0_2