比如相关性系数，主观上可以选择0.9以上算高。或者0…Mutual Information一般不直接比大小。单纯比较I(X...
那么根据data，你可以找出两两之间的mutual information是多大，e.g.I(X1,X2)=0.01,I(X1,X3)=10...
This framework minimizes the CCMI (Constrained Conditional Mutual Information) loss function, which represents the conditional mutual information between input augmented samples of the same sample and the output representations of the encoder while the prior distribution of representations is constrained. By...
where the expectation is taken over the joint distribution ofXandY. Herep(x,y)is the joint probability density function ofXandY,p(x)andp(y)are the marginal probability density functions ofXandYrespectively. In general, a higher mutual information between the dependent variable (or label) and an...
Changed region extraction to use the unfold function. Also added stri… Jan 19, 2021 setup.py Add setup files. Jan 17, 2021 Repository files navigation README MIT license Region Mutual Information loss PyTorch implementation of the Region Mutual Information Loss for Semantic Segmentation. The purpos...
. The information loss paradox in terms of the Page curve can be understood as follows. The fine grained entropy of Hawking radiation is identified by the von Neumann entropy of quantum fields on the region R outside the black hole. Now assuming the state on the full Cauchy slice to be ...
本文是对DMI的一些笔记,参考论文 1911.00272.pdf (arxiv.org)和L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise (neurips.cc)DMI是对香农互信息的推广,与香…
论文全称《Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning》。文中并未提及算法的名称,“VIMIM”是根据论文题目给的缩写。这是一篇比较原始的介绍state empowerment的文章,是基于互信息的skill discovery的前身。其特点是:(1)首先定义了state empowerment,即给定current state,next ...
Normalized mutual information (NMI) is leveraged as a modulator for calibrating uncertainty bounds derived from CI based on a weighted loss function. Our simulation results show an inverse correlation between inherent predictive uncertainty and NMI throughout the model's training. The framework ...
Hence, we propose a structure-aware Mutual Information based loss-function DMI (Discourse Mutual Information) for training dialog-representation models, that additionally captures the inherent uncertainty in response prediction. Extensive evaluation on nine diverse dialog modeling tasks shows that our ...