From b8142ed805da40ce1ffeccf540b9e7e69b812598 Mon Sep 17 00:00:00 2001 From: kazewong Date: Sat, 18 May 2024 16:26:54 -0400 Subject: [PATCH] Update SBI.html and SBIexamples.html --- reveal/NanoGrav2024/SBI.html | 87 +----------------------------------- 1 file changed, 2 insertions(+), 85 deletions(-) diff --git a/reveal/NanoGrav2024/SBI.html b/reveal/NanoGrav2024/SBI.html index aaca4991520..0908e4aaf13 100644 --- a/reveal/NanoGrav2024/SBI.html +++ b/reveal/NanoGrav2024/SBI.html @@ -50,90 +50,7 @@

What do we train?

Normalizing flow

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Single GW event inference

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Data

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Source properties

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Neural posterior estimation for gravitational wave

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Population inference

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If you believe us, then most of the bbhs are from cluster!(I don't)

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Let's take a moment and think

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why the first example is more believable?

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Lesson from two SBI scenarios

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Perks of SBI

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  1. Fast inference
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  3. Low retuning human effort
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  5. Flexible assumptions
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Dangers of SBI

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  1. "Why is my mass negative"
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  3. Are we really winning?
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  5. Retraining cost
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Fixed model, changing data -> Good

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Fixed data, change model -> Bad

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