Auto Encoding Variational Bayes
Auto-Encoding Variational Bayes (AEVB) is a powerful framework in modern machine learning that combines principles from deep learning and Bayesian inference. It provides a probabilistic approach to representation learning, allowing complex data distributions to be modeled efficiently. By leveraging neural networks, variational inference, and stochastic optimization, AEVB has become the foundation for variational autoencoders (VAEs), … Read more