Graphical models provide a robust framework for representing the conditional independence structure between variables through networks, enabling nuanced insight into complex high-dimensional data.

Probabilistic graphical models are a powerful technique for handling uncertainty in machine learning. The course will cover how probability distributions can be represented in graphical models, how ...

Graphical models form a cornerstone of modern data analysis by providing a visually intuitive framework to represent and reason about the complex interdependencies among variables. In particular, ...

Customers are considering applications for AI inference and want to evaluate multiple inference accelerators. As we discussed last month, TOPS do NOT correlate with inference throughput and you should ...

Google researchers have warned that large language model (LLM) inference is hitting a wall amid fundamental problems with memory and networking problems, not compute. In a paper authored by ...