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Simulation-Based Inference for Cosmological Data Analysis

Bayesian Inference Fundamentals → Capstone Project: SBI for Cosmological Parameters

This learning path equips graduate students in cosmology with the skills to use simulation-based inference (likelihood-free inference) for cosmological parameter estimation. It covers forward modeling, emulators, approximate Bayesian computation, and neural network approaches, culminating in applied projects that constrain cosmological parameters from simulated data.

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15 steps · 15 nodes · 4 stages

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Path Steps

15 steps · 4 stages. Click any step to inspect it and see it on the Path Map.

Stage 1

Foundation

4 steps

Stage 2

Core Concepts

4 steps

Stage 3

Advanced Topics

4 steps

Stage 4

Specialization

3 steps

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