Automatic Variational Inference in Stan

Variational inference is a scalable technique for approximate Bayesian inference. Deriving variational inference algorithms requires tedious model-specific calculations; this makes it difficult to automate. We propose an automatic variational inference algorithm, automatic differentiation variational inference (ADVI). The user only provides a Bayesian model and a dataset; nothing else. We make no conjugacy assumptions and support a broad class of models. The algorithm automatically determines an appropriate variational family and optimizes the variational objective. We implement ADVI in Stan (code available now), a probabilistic programming framework. We compare ADVI to MCMC sampling across hierarchical generalized linear models, nonconjugate matrix factorization, and a mixture model. We train the mixture model on a quarter million images. With ADVI we can use variational inference on any model we write in Stan

Automatic Differentiation Variational Inference

Probabilistic modeling is iterative. A scientist posits a simple model, fits it to her data, refines it according to her analysis, and repeats. However, fitting complex models to large data is a bottleneck in this process. Deriving algorithms for new models can be both mathematically and computationally challenging, which makes it difficult to efficiently cycle through the steps. To this end, we develop automatic differentiation variational inference (ADVI). Using our method, the scientist only provides a probabilistic model and a dataset, nothing else. ADVI automatically derives an efficient variational inference algorithm, freeing the scientist to refine and explore many models. ADVI supports a broad class of models-no conjugacy assumptions are required. We study ADVI across ten different models and apply it to a dataset with millions of observations. ADVI is integrated into Stan, a probabilistic programming system; it is available for immediate use

Genetic Screening of Couples with Recurrent Spontaneous Abortion

The aim of this study was to determine the chromosomal abberations and their incidence in non-consanguineous couples with a history of two or more than two spontaneous abortion. In the study, we carried out cytogenetic analysis on 434 couples. Patients detected with chromosome abnormality were evaluated according to their pedigree analysis, and also patients’ relatives were screened for the same abnormality. Peripheral blood were taken from patients, then performed with lymphocyte culture and stained by binded using Giemsa-banding method. For each individual, 20-30-cells chromosomes were counted and around 5-10 well-binded metaphase chromosomes were karyotyped for numerical and structural chromosomal aberrations. Of 434 couples investigated, 30 (6.91%) were found to have chromosomal abnormality, in one of couples partners. In 13 of couples (2.99%), one of partners was found to be balanced translocation carrier. Of these, 7 (1.61%)were found to be reciprocal carrier, while 6 (1.38%) Robertsonian-type balanced translocation carrier. Gonadal mosaicism was found in 3 couples (0.69%), pericentric 9 inversion in 8 couples (1.85 %), while 6 couples showed different chromosomal structure from each other. These chromosomal aberrations may cause of abortion due to high incidence in general population

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Atom clusters and vibrational excitations in chemically-disordered Pt357Fe

Inelastic nuclear resonant scattering spectra of Fe-57 atoms were measured on crystalline alloys of Pt3Fe-57 that were chemically disordered, partially ordered, and L1(2) ordered. Phonon partial density of states curves for Fe-57 were obtained from these spectra. Upon disordering, about 10% of the spectral intensity underwent a distinct shift from 25 to 19 meV. This change in optical modes accounted for most of the change of the vibrational entropy of disordering contributed by Fe atoms, which was (+0.10 +/- 0.03) k(B) (Fe atom)(-1). Prospects for parametrizing the vibrational entropy with low-order cluster variables were assessed. To calculate the difference in vibrational entropy of the disordered and ordered alloys, the clusters must be large enough to account for the abundances of several of the atom configurations of the first-nearest-neighbor shell about the Fe-57 atoms