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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
PDF slides
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
PDF slides
3.2 Introduction to the sbi toolkit
3.2 Introduction to the sbi toolkit
3.2 Introduction to the sbi toolkit
Jan Bölts
Notebook (GitHub)
3.3 Troubleshooting sbi
3.3 Troubleshooting sbi
3.3 Troubleshooting sbi
Jan Bölts
Notebook (GitHub)
3.4 Bayesian workflow
3.4
3.4 Bayesian workflow
Jan Bölts
Notebook (GitHub)
Extras (day 3)
3.5 Bayesian model comparison
3.5 Bayesian model comparison
3.5 Bayesian model comparison
Jan Bölts
PDF slides
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
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