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The team’s award-winning paper “covers a critical missing piece of our understanding of visual generative models and will likely inspire future important theory work in this area,” the awards committee wrote. The committee further noted that the authors “provide an explanation of this phenomenon in terms of architectural inductive biases by making a connection to ideas from harmonic analysis via ‘geometry-adaptive harmonic representations.’”

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