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Given an inverse problem with a normalizing flow prior, we wish to estimate the distribution of the underlying signal conditioned on the observations.
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Kabkab, M., Samangouei, P., and Chellappa, R · 2018
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Variational inference for computational imaging inverse problems
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Improving exploration in soft-actor-critic with normalizing flows policies
Ward, P. N., Smofsky, A., and Bose, A. J · 2019
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Projected latent markov chain monte carlo: Conditional sampling of normalizing flows, 2020
Cannella, C., Soltani, M., and Tarokh, V · 2020
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Information-theoretic lower bounds for compressive sensing with generative models
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