bimdsm
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- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models (0.84)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Gradient Descent (0.54)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.46)
Table A: FID on CIFAR10. means averaged by 5 runs. Methods with use comparable networks. Method FID FID-ES Flow-CE [ 1*] 37.30 - V AE-EBL VM[2*] 30.1 - MDSM [34] - 31.7 MDSM
We thank all reviewers for their valuable comments. Below, we first address the common concerns and then answer the detailed questions. It leads to smaller bias (see Fig. A), which also agrees with Thm. 2. First, introducing latent variables can improve the sample quality (w.r.t. Indeed, we update Tab. 2 and obtain Tab. As stated in L290, a similar protocol is adopted in MDSM [34].
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- Asia > China > Beijing > Beijing (0.04)
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