4. Mutual Information http://fourier.eng.hmc.edu/e176/lectures/probability/node6.html 5. Gibbs' Inequality H(P)=−∑iPilogPi≤CrossEntropy(P,Q)=−∑iPilogQi 6. Cross Entropy 7. KL divergence 其他link: pytorch 公式 nn.KLDivLoss() ...
deffenchel_dual_loss(l,m,measure=None):'''Args:l: Local feature map. 这里指没编码前的特征图,但其实也经历了和编码结构一样的压缩m: Multiple globals feature map. 编码后的特征向量,目标就是使正例中的两者互信息最大measure: f-divergence measure. 可以看最下面一系列'''N,units,n_locals=l.size...
Our bounds provide an information-theoretic understanding of generalization in the so-called class of variational classifiers, which are regularized by a Kullback–Leibler (KL) divergence term. These results give theoretical grounds for the highly popular KL term in variational inference methods that ...
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The mutual information can also be calculated as the KL divergence between the joint probability distribution and the product of the marginal probabilities for each variable. If the variables are not independent, we can gain some idea of whether they are ‘close’ to being independent by considerin...
The mutual information of a joint distribution p(X,Y) is the KL-divergence between the joint distribution and the product of the marginal distributions or equivalently the difference in uncertainty of r.v X given that we know Y. Mutual information is an important metric since its a measure ...
DIM draws inspiration from the infomax principle, a guideline for learning good representations by maximizing the mutual information between the input and output of a neural network. In this setting, the mutual information is defined as the KL-divergence between the joint distribut...
GitHub - ZJULearning/RMI: This is the code for the NeurIPS 2019 paper Region Mutual Information Loss for Semantic Segmentation.. 一、要解决的问题(Why) 语义分割是计算机视觉中的一个基本问题,其目标是为图像中的每个像素分配语义标签。最近,强大的卷积神经网络(例如,VGGNet [33]、ResNet [14]、Xception...
为此,作者试图通过一种增强图的训练方式提高CF的表现能力,将节点embedding的学习和图结构的学习进行互相增强。 附上原文和代码链接: Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximizationdl.acm.org/doi/pdf/10.1145/3404835.3462928...
In the case of VCCA, the KL divergence coefficient is set so that its reconstruction quality matches MIAAE. TMIAAE is a modified MIAAE model that adds negative sampling and triplet loss to the objective function. DLSAAE is a modified model that extends LSAAE with decoupling to provide the ...