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Designing Perceptual Puzzles by Differentiating Probabilistic Programs
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DescriptionWe design new examples of visual illusions like "The Dress" by finding "adversarial examples" for principled models of human perception — specifically probabilistic models, which treat vision as Bayesian inference. To perform this search efficiently, we design a differentiable probabilistic programming language, exposing MCMC inference as a first-class differentiable function.