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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) cover image

AI Trends 2023: Causality and the Impact on Large Language Models with Robert Osazuwa Ness - #616

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

NOTE

Amortized Inference for Causal Structure Learning: Using Simulators for Causal Discovery

A paper by Lars Lurgs and Bernard Shokoff called amortized inference for causal structure learning. They were using simulators to simulate the simulate data. These are ways that people encode knowledge often from physical domains about causal mechanism. And so using that to create the inductive bias for a causal discovery or any other algorithm.

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