# Workshop

Conclusion & Discussion

**Francois Lanusse**

**Simons Foundation / CNRS**

# I can't believe we don't have a solution for that!?!

# Data Reduction with AI

## Has Deep Learning Really Solved Image Processing?

**Credit**: Marc's Thursdays Talk

*In total we have examined ∼ 50, 000 objects. On average one in 150 of the objects with [high] probability from the ResNet model is deemed a lens candidate through human inspection.*

=> At the rate of LSST, this would mean needing human inspection for O(10^7) candidates

## Deep Learning Representations Are Not Very Deep...

**Credit**: Tanaka's Thursday Talk

**Credit**: Anna's Thursday Talk

# How do we build AI systems with a deep understanding of the data?

# Pushing the limits of physical inference with AI

## Simulation-Based Inference Works!

**Credit**: Konstantin's talk

**Important point**: If your simulator matches your Bayesian model, traditional MCMC should be equivalent to SBI

**Credit**:

Jennifer's talk

SBI is fast!

# This is very exciting to make better use of available information!

Lu et al. 2023

## We May Also be Able to Perform Field-Level Inference Explicitly!

**Credit**: Alan's talk

**Credit**: Yin's talk

**Credit**: Adrian's talk

# Emulating Complex Simulations

**Credit**: Ben's talk

It's not necessarily an easy problem!

## But can we build accurate enough models?

**Credit**: Paco's talk

## And it's even worse than that!

Gatti, Jeffrey, Whiteway et al. (2023)

Impact of source clustering in weak lensing simulations

Impact of baryons on the power spectrum

Chisari et al. (2018)

# What Solutions Can we Imagine for This Model Misspecifiation Problem ?

# What would *you* like to be able to do with AI?

# Francois' Answers

# How do we build AI systems with a deep understanding of the data?

## Creating a Deeper Connection to the Physics

## Emergent Features in Self-Supervised Represenation

Dino v2

# Towards more flexible architectures

**Credit**: Mariel's talk

# What Solutions Can we Imagine for This Model Misspecifiation Problem ?

## Hybrid Parametrization of Forward Model with Nuisance Parameters

Dai et al. 2018

Dai & Seljak 2021

#### AI4Phys

By eiffl

# AI4Phys

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