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We present the information-ordered bottleneck (IOB), a neural layer designed to adaptively compress data into latent variables ordered by likelihood maximization.
The large-sample distribution of the likelihood ratio for testing composite hypotheses
Samuel S Wilks · 1938
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Estimating the intrinsic dimension of datasets by a minimal neighborhood information
Fully nested neural network for adaptive compression and quantization
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Learning transferable visual models from natural language supervision
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Masked autoencoders are scalable vision learners
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