Asim Shah·Sep 24Deep Generative Models, Part 2: What Is an Autoencoder Actually Learning?Part 2 of a series on Deep Generative Models — Overview → Autoencoders → VAEs → Diffusion Models
Harshini Subramanyam·Aug 24Inside the Magic: How Generative AI Creates the NewFrom GANs to Transformers — the algorithms that imagine, learn, and create
Chougaleharsh·Aug 15VAE vs GAN: A Comparative Study of Generative ModelsUnderstanding how generative models learn, represent, and create new data
Francis Benistant·Jun 21Unit Normalization: Keras’ Latest Normalization Technique for Improving Neural Network TrainingIntroduction:
InGenerative AIbySubhash Jugran·Jun 7VAEs and GANs: Two Classic Generative AI Ideas That Still Feel Like MagicHow hidden maps and creative competition taught machines to generate.
Visalaxi Hari·Jun 2Statistical Evaluation Metrics for Generative AI: Assessing Synthetic Tabular Data, Text…Generative AI models play a substantial role in generating content such as text, image, and synthetic tabular data. The quality of the…
Ioannis Tsiokos·Feb 22State Aggregation and Latent Space CollapseWhen Finer Representations Destroy Stable Features
Naren Suri·Jan 14The Geometry of Creation — Part 2Mastering the Five Pillars of Stochastic Machine Learning
