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Unnormalised latent variable models are a broad and flexible class of statistical models.
Maximum likelihood from incomplete data via the EM algorithm
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Stochastic gradient estimation strategies for Markov random fields
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Jacobian-free Newton–Krylov methods: a survey of approaches and applications
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Using fast weights to improve persistent contrastive divergence
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A family of computationally efficient and simple estimators for unnormalized statistical models
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Bregman divergence as general framework to estimate unnormalized statistical models
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Bayesian reasoning and machine learning
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Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics
Gutmann, M. and Hyvärinen, A. (2012) · 2012
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Variational Bayesian inference with stochastic search
Paisley, J., Blei, D., and Jordan, M. (2012) · 2012
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Stochastic variational inference
Hoffman, M. D., Blei, D. M., Wang, C., and Paisley, J. (2013) · 2013
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Stochastic gradient VB and the variational auto-encoder
Kingma, D. P. and Welling, M. (2013) · 2013
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The Poisson transform for unnormalised statistical models
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A neural probabilistic model for context based citation recommendation
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Structured prediction energy networks
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Estimation of high-dimensional graphical models using regularized score matching
Lin, L., Drton, M., and Shojaie, A. (2016) · 2016
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Collective noise contrastive estimation for policy transfer learning
Zhang, W., Paquet, U., and Hofmann, K. (2016) · 2016
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Conditional Noise-Contrastive Estimation of Unnormalised Models
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