From a8ade9aebc53c1b640cbeaee1386724ba2319cd1 Mon Sep 17 00:00:00 2001 From: Kaze Wong Date: Tue, 18 Jul 2023 20:46:32 -0400 Subject: [PATCH] update --- slides/amaldi2023/SBI.html | 23 +++++++++++++++++++++++ slides/amaldi2023/hybrid.html | 9 ++++++++- slides/amaldi2023/model.html | 34 +++++++++++++++++++++++++++------- 3 files changed, 58 insertions(+), 8 deletions(-) diff --git a/slides/amaldi2023/SBI.html b/slides/amaldi2023/SBI.html index 4b18d9b3544..02997347b79 100644 --- a/slides/amaldi2023/SBI.html +++ b/slides/amaldi2023/SBI.html @@ -2,8 +2,31 @@

Simulation-based inference

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Simulate, train, compare

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Single event inference

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Data

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Source properties

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Single event inference

diff --git a/slides/amaldi2023/hybrid.html b/slides/amaldi2023/hybrid.html index 267d40cccde..4fc49bfaf88 100644 --- a/slides/amaldi2023/hybrid.html +++ b/slides/amaldi2023/hybrid.html @@ -5,7 +5,7 @@

Hybrid method

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Jax - python on steroid

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Infrastructure around AI is just as cool

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flowMC - Normalizing flow enhanced MCMC

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How does it work? Normal MCMC

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How does it work? Building normalizng flow

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Challenges for population analysis

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  1. Growingly difficult to build models
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  3. Hard to go to high dimension
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  5. Powered by smart people (short in supply)
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Flexible population model

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It works, but unstable with selection function?

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Symbolic regression

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Closing the loop

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