Program (1)

Day 1

1.1 Simulators and inference

1.1 Simulators and inference

1.1 Simulators and inference

Álvaro Tejero-Cantero

Introduction to sbi: simulation & inference

1.2 Practical: from ABC to SBI

1.2

1.2 Practical: from ABC to SBI

Álvaro Tejero-Cantero

Notebook (GitHub)

1.3 Invited lecture: SBI in neuroscience

1.3

1.3 Invited lecture: SBI in neuroscience

Pedro J. Gonçalves

Day 2

2.1 (Conditional) density estimation

2.1 (Conditional) density estimation

2.1 (Conditional) density estimation

Michael Deistler

Notebook (GitHub)

2.2 Sequential neural posterion estimation explained

2.2 Sequential neural posterion estimation explained

2.2 Sequential neural posterion estimation explained

Michael Deistler

Notebook (GitHub)

2.3 SNLE and SNRE

2.3

2.3 SNLE and SNRE

David Greenberg

Notebook (GitHub)

Day 3

3.1 Benchmarking sbi

3.1

3.1 Benchmarking sbi

Jan-Matthis Lückmann

3.2 Introduction to the sbi toolkit

3.2 Introduction to the sbi toolkit

3.2 Introduction to the sbi toolkit

Notebook (GitHub)

3.3 Troubleshooting sbi

3.3 Troubleshooting sbi

3.3 Troubleshooting sbi

Notebook (GitHub)

3.4 Bayesian workflow

3.4

3.4 Bayesian workflow

Notebook (GitHub)

Extras (day 3)

3.5 Bayesian model comparison

3.5 Bayesian model comparison

3.5 Bayesian model comparison

3.6 Bring your own simulator and apply sbi to your problem!

3.6 Bring your own simulator and apply sbi to your problem!

3.6 Bring your own simulator and apply sbi to your problem!

Participant led!

N/A