495 research outputs found
Patterns of Scalable Bayesian Inference
Datasets are growing not just in size but in complexity, creating a demand
for rich models and quantification of uncertainty. Bayesian methods are an
excellent fit for this demand, but scaling Bayesian inference is a challenge.
In response to this challenge, there has been considerable recent work based on
varying assumptions about model structure, underlying computational resources,
and the importance of asymptotic correctness. As a result, there is a zoo of
ideas with few clear overarching principles.
In this paper, we seek to identify unifying principles, patterns, and
intuitions for scaling Bayesian inference. We review existing work on utilizing
modern computing resources with both MCMC and variational approximation
techniques. From this taxonomy of ideas, we characterize the general principles
that have proven successful for designing scalable inference procedures and
comment on the path forward
Accelerating MCMC via Parallel Predictive Prefetching
We present a general framework for accelerating a large class of widely used
Markov chain Monte Carlo (MCMC) algorithms. Our approach exploits fast,
iterative approximations to the target density to speculatively evaluate many
potential future steps of the chain in parallel. The approach can accelerate
computation of the target distribution of a Bayesian inference problem, without
compromising exactness, by exploiting subsets of data. It takes advantage of
whatever parallel resources are available, but produces results exactly
equivalent to standard serial execution. In the initial burn-in phase of chain
evaluation, it achieves speedup over serial evaluation that is close to linear
in the number of available cores
Excitability Constraints on Voltage-Gated Sodium Channels
We study how functional constraints bound and shape evolution through an analysis of mammalian voltage-gated sodium channels. The primary function of sodium channels is to allow the propagation of action potentials. Since Hodgkin and Huxley, mathematical models have suggested that sodium channel properties need to be tightly constrained for an action potential to propagate. There are nine mammalian genes encoding voltage-gated sodium channels, many of which are more than ≈90% identical by sequence. This sequence similarity presumably corresponds to similarity of function, consistent with the idea that these properties must be tightly constrained. However, the multiplicity of genes encoding sodium channels raises the question: why are there so many? We demonstrate that the simplest theoretical constraints bounding sodium channel diversity—the requirements of membrane excitability and the uniqueness of the resting potential—act directly on constraining sodium channel properties. We compare the predicted constraints with functional data on mammalian sodium channel properties collected from the literature, including 172 different sets of measurements from 40 publications, wild-type and mutant, under a variety of conditions. The data from all channel types, including mutants, obeys the excitability constraint; on the other hand, channels expressed in muscle tend to obey the constraint of a unique resting potential, while channels expressed in neuronal tissue do not. The excitability properties alone distinguish the nine sodium channels into four different groups that are consistent with phylogenetic analysis. Our calculations suggest interpretations for the functional differences between these groups
Notes on Recent Cases
Notes on recent cases by Henry Hasley, J. P. Berscheid, J. J. Canty, J. Angelino, F. Earl Lamboley, D. M. Donahue, Marc Wonderlin, and A. J. DeDario
Notes on Recent Cases
Notes on recent cases by J. S. Angelino, Marc Wonderlin, W. S. McCray, John P. Berscheid, J. J. Canty, J. J. Lyons, R. C. Kuehl, D. M. Donahue, M. E. McGcogehgan, G. L. Housley, Thomas J. Jones, Jr., and F. Earl Lamboley
Effects of plasma current on nonlinear interactions of ITG turbulence, zonal flows and geodesic acustic modes
Consanguinity and polygenic diseases: a model for antibody deficiencies
Primary immunodeficiencies represent a heterogeneous group of disorders of the immune system, predisposing to various types of infections. Among them, common variable immunodeficiency is the most common symptomatic antibody deficiency. It includes several different forms characterized by defects in the terminal stage of B lymphocyte differentiation, leading to markedly reduced immunoglobulin serum levels and increased susceptibility to bacterial infections. The clinical phenotype is complex, including autoimmunity, granulomatous inflammation, lymphoproliferative disorders and malignancies. Rare autosomal recessive mutations in a number of single genes have recently been reported. However, the underlying genetic defects remain unknown in the majority of cases. In order to seek new genes responsible for the disease, we studied a consanguineous Italian family through exome sequencing combined with homozygosity mapping. Six missense homozygous variants passed our filtering selection and at least two of them were associated with some aspects of the pathological phenotype. Our data remark the complexity of immune system disorders and emphasize the difficulty to understand the significance of genetic results and their correlation with the disease phenotype
Plasma elongation and magnetic shear effects in nonlinear simulations of ITG-zonal flow turbulence
DAMPAK KENAIKAN NILAI JUAL OBYEK PAJAK (NJOP) ATAS BUMI DAN BANGUNAN ERAHADAP TINGKAT PENERIMAAN PADA BADAN PENDAPATAN DAERAH KOTA SEMARANG PERIODE 2015-2017
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