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allepalma authored Jan 9, 2025
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# IMPA

# Image Perturbation Autoencoder (IMPA)

**Image Perturbation Autoencoder** (IMPA) is a model designed for style transfer on images of cells treated with various perturbations. IMPA is a Generative Adversarial Network (GAN) based on an autoencoder model. Images of control cells are encoded into a high-dimensional latent space and decoded conditioned on a perturbation representation. The decoder's output is used to deceive a discriminator model into classifying the decoded cells as truly coming from the target perturbation. In this way, our approach allows us to predict how a control cell would look had it been perturbed by a given treatment.
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