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Deep Generative Models in Medicine - CGSI 2023

Computational Genomics Summer Institute CGSI via YouTube

Overview

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Explore deep generative models in medicine through this 32-minute conference talk from the Computational Genomics Summer Institute. Delve into the fundamentals of generative models, their applications in healthcare, and advanced concepts like robustness, interpretability, and missing data imputation. Examine the potential of large language models in biomedical text generation and mining. Investigate diffusion models, their training processes, and the Diffusion ELBO. Learn about multivariate diffusions, automatic mean and covariance calculations, and conditioning techniques. Gain insights into recent advancements in molecular discovery using generative models and their challenges in the biomedical field.

Syllabus

Intro
What is a generative model?
Robustness
Interpretability
Filling in Missing Data
Large Language Models
Generation
Diffusions get good likelihoods
What is a diffusion model?
How do you train a diffusion model?
Diffusion ELBO
What types of corruptions/inference SDES?
Derivation for critically damped langevin
Do differences matter?
Other processes?
A multivariate ELBO
Automatic mean + covariance
Is the generic approach any slower?
The stationary distribution
Automatic multivariate diffusion training
Similar results with a fraction of the parameters
Conditioning in a Diffusion
Reference

Taught by

Computational Genomics Summer Institute CGSI

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