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We develop a likelihood free inference procedure for conditioning a probabilistic model on a predicate.
Replica monte carlo simulation of spin-glasses
Swendsen, R. H. and Wang, J.-S · 1986
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Fuzzy sets and fuzzy logic , volume 4
Klir, G. and Yuan, B · 1995
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Conditioning as disintegration
Chang, J. T. and Pollard, D · 1997
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Inferring coalescence times from dna sequence data
Tavaré, S., Balding, D. J., Griffiths, R. C., and Donnelly, P · 1997
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Inverse rendering for computer graphics
Marschner, S. R. and Greenberg, D. P · 1998
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Inference of population history using a likelihood approach
Weiss, G. and von Haeseler, A · 1998
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An introduction to variational methods for graphical models
Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., and Saul, L. K · 1999
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Basic concepts of continuous logics
Levin, V · 2000
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Physionet: a web-based resource for the study of physiologic signals
Moody, G. B., Mark, R. G., and Goldberger, A. L · 2001
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Approximate bayesian computation in population genetics
Beaumont, M. A., Zhang, W., and Balding, D. J · 2002
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An introduction to mcmc for machine learning
Andrieu, C., De Freitas, N., Doucet, A., and Jordan, M. I · 2003
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Markov chain monte carlo without likelihoods
Marjoram, P., Molitor, J., Plagnol, V., and Tavaré, S · 2003
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A probabilistic model for predicting hypoglycemia in type 2 diabetes mellitus: The diabetes outcomes in veterans study (doves)
Murata, G. H., Hoffman, R. M., Shah, J. H., Wendel, C. S., and Duckworth, W. C · 2004
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Parallel tempering: Theory, applications, and new perspectives
Earl, D. J. and Deem, M. W · 2005
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Cute: a concolic unit testing engine for c
Sen, K., Marinov, D., and Agha, G · 2005
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Glycemic variability: a hemoglobin a1c–independent risk factor for diabetic complications
Brownlee, M. and Hirsch, I. B · 2006
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Markov logic networks
Richardson, M. and Domingos, P · 2006
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Problog: A probabilistic prolog and its application in link discovery
De Raedt, L., Kimmig, A., and Toivonen, H · 2007
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1 blog: Probabilistic models with unknown objects
Milch, B., Marthi, B., Russell, S., Sontag, D., Ong, D. L., and Kolobov, A · 2007
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Sequential monte carlo without likelihoods
Sisson, S. A., Fan, Y., and Tanaka, M. M · 2007
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A short introduction to probabilistic soft logic
Kimmig, A., Bach, S., Broecheler, M., Huang, B., and Getoor, L · 2012
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Adaptive approximate bayesian computation for complex models
Lenormand, M., Jabot, F., and Deffuant, G · 2013
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The no-u-turn sampler: adaptively setting path lengths in hamiltonian monte carlo
Hoffman, M. D. and Gelman, A · 2014
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Venture: a higher-order probabilistic programming platform with programmable inference
Mansinghka, V., Selsam, D., and Perov, Y · 2014
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Black box variational inference
Ranganath, R., Gerrish, S., and Blei, D · 2014
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A new approach to probabilistic programming inference
Wood, F., Meent, J. W., and Mansinghka, V · 2014
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