BriefGPT.xyz
Jun, 2024
可识别的可交换机制用于因果结构和表示学习
Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning
HTML
PDF
Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel
TL;DR
通过交替可识别机制(IEM)统一了交换性数据和因果结构学习的框架,提出了新的可识别性结果,并希望为因果表示学习的进一步研究铺平道路。
Abstract
Identifying
latent representations
or
causal structures
is important for good generalization and downstream task performance. However, both fields have been developed rather independently. We observe that several
→