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Learning Bayesian Statistics
How to Choose & Use Priors, with Daniel Lee
Dec 20, 2023
Daniel Lee, an expert in Bayesian statistics, discusses the challenges in accurately depicting situations based on multiple data pieces. He explores identifying hidden objects, applying vision stats, building complex models in Bayesian statistics, and struggles in choosing priors.
09:06
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Quick takeaways
- The Fourier transform can be used to align radar images and distinguish actual targets from overlapping readings in US Navy applications.
- Building complex models and incorporating measurement models is important in accurately describing phenomena, and understanding the role of priors in Bayesian modeling helps make informed choices in choosing priors.
Deep dives
Using Bayesian stats for Data Fusion in US Navy applications
In the podcast, the speaker discusses the application of Bayesian statistics for Data Fusion in US Navy applications. The challenge they faced was accurately depicting the situation where an aircraft carrier is surrounded by multiple ships, all with radars pointing at the same thing. The problem arises when the radar readings from the ships slightly differ, causing multiple identifications of the same target, leading to uncertainty and potential misinterpretation. The speaker explains that by using the Fourier transform of radar images and stacking them on top of each other, it was possible to align the images and distinguish actual targets from the overlapping readings.
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Discover
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Listen to the best highlights from the podcasts you love and dive into the full episode