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Differentially Private Diffusion Models Generate Useful Synthetic Images.

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Monte Carlo Sort for unreliable human comparisons.. CoRR, (2016)Decoding Decoders: Finding Optimal Representation Spaces for Unsupervised Similarity Tasks., , , , и . ICLR (Workshop), OpenReview.net, (2018)Differentially Private Diffusion Models Generate Useful Synthetic Images., , , , , , , , , и . CoRR, (2023)A study on the plasticity of neural networks., , , , , , и . CoRR, (2021)Batch Normalization Biases Deep Residual Networks Towards Shallow Paths, и . (2020)cite arxiv:2002.10444.ConvNets Match Vision Transformers at Scale., , , и . CoRR, (2023)The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study., , , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 5042-5051. PMLR, (2019)Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error., , , , и . CoRR, (2021)On the Origin of Implicit Regularization in Stochastic Gradient Descent., , , и . ICLR, OpenReview.net, (2021)Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation., , , , , , и . ICLR, OpenReview.net, (2023)