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Published inTDS ArchiveThe Bias-Variance TradeoffA (Nearly) Stats-Free AdventureDec 10, 20211Dec 10, 20211
Published inTDS ArchiveBayesian ThinkingHow a Statistician Reacts to Life on VenusSep 19, 20206Sep 19, 20206
Published inTDS ArchiveHow to Build a DCGAN with PyTorchA Jump-Start GAN TutorialJun 26, 20203Jun 26, 20203
Published inTDS ArchivePyTorch and GANs: A Micro TutorialBuilding the Simplest of GANs in PyTorchJun 22, 20205Jun 22, 20205
Published inTDS ArchiveAutoencoding Generative Adversarial NetworksHow the AEGAN architecture stabilizes GAN training and prevents mode collapseApr 18, 20204Apr 18, 20204
Published inTDS Archivefrom sklearn import *…and other dead-giveaways that you’re a fake data scientistMar 22, 202024Mar 22, 202024
Published inTDS ArchiveWhy Do GANs Need So Much Noise?Visualizing how GANs learn in low-dimensional latent spacesFeb 26, 20201Feb 26, 20201
Published inTDS ArchiveGANs and Inefficient MappingsHow GANs tie themselves in knots and why that impairs both training and qualityJan 27, 20205Jan 27, 20205
Published inTDS ArchiveTraining a GAN to Sample from the Normal DistributionVisualizing the Very Basics of Generative Adversarial NetworksJan 12, 20202Jan 12, 20202