Tag variational inference
In the rapidly evolving field of machine learning, understanding variational inference and its components can become increasingly intricate. A recent study titled “Tighter Variational Bounds are Not Necessarily Better” questions some commonly held beliefs about evidence lower bounds (ELBOs) and… Continue Reading →
In the ever-evolving world of statistics and machine learning, the quest for efficient and accurate methods for estimating posterior distributions is relentless. Among these methods, variational inference has gained significant traction. However, an important question arises: How can we effectively… Continue Reading →
Probabilistic modeling forms the foundation of scientific analysis, allowing researchers to describe complex phenomena and make predictions based on data. However, fitting complex models to large datasets has always been a challenging and time-consuming process. The advent of automatic differentiation… Continue Reading →