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#12: Deep Prasad - How to Build a Physics-Fluent AI System
First Principles with Christian Keil
Learning Coherent Images through Diffusion Models
Diffusion models incrementally add noise to a model and train a loss function to generate coherent images from noisy ones. By teaching AI to work backwards from noisy images to original ones, it learns to create any coherent image. Injecting noise into the system forces it to come up with realistic constructions. Combining crystal diffusion and variational autoencoder results in a model that improves with more data.
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