Tag
variational-inference
- Oct 15, 2026 Variational Inference and the Evidence Lower Bound Why maximizing a lower bound replaces integrating a posterior, how mean-field updates are derived coordinate by coordinate, and what the bound systematically understates. machine learning
- May 19, 2026 The Evidence Lower Bound as a Latent Variable Objective How the intractable marginal likelihood of a latent variable model is split into a reconstruction term and a KL term, and what each term pushes the encoder to do. deep learning
- May 9, 2024 Posterior Collapse and the KL Term That Wins Why a latent variable model can learn to ignore its latents entirely, how the KL term competes with reconstruction, and which interventions change the balance. deep learning
- Nov 6, 2023 The Reparameterization Trick and Gradient Flow Through Sampling Why a sampling operation blocks backpropagation, how the score-function estimator works around it, and what the reparameterized estimator changes about gradient variance. deep learning