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nature methods | 通过稀疏自编码器基于蛋白质语言模型发现可解释特征
字典向量(dᵢ):位于原始嵌入空间(embedding space)中,存储在解码器矩阵(decoder matrix)的行中; 激活值(fᵢ):决定该特征对最终重构的贡献程度。 其中,b是偏置项,是学习到的字典的大小。 SAEs将单个氨基酸的嵌入向量转换为一个具有更大尺寸和稀疏性的向量。
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