9,115 research outputs found
Bayesian Learning and Predictability in a Stochastic Nonlinear Dynamical Model
Bayesian inference methods are applied within a Bayesian hierarchical
modelling framework to the problems of joint state and parameter estimation,
and of state forecasting. We explore and demonstrate the ideas in the context
of a simple nonlinear marine biogeochemical model. A novel approach is proposed
to the formulation of the stochastic process model, in which ecophysiological
properties of plankton communities are represented by autoregressive stochastic
processes. This approach captures the effects of changes in plankton
communities over time, and it allows the incorporation of literature metadata
on individual species into prior distributions for process model parameters.
The approach is applied to a case study at Ocean Station Papa, using Particle
Markov chain Monte Carlo computational techniques. The results suggest that, by
drawing on objective prior information, it is possible to extract useful
information about model state and a subset of parameters, and even to make
useful long-term forecasts, based on sparse and noisy observations
Experimental verification of a simplified vee-tail theory and analysis of available data on complete models with vee tails
Streaming, Distributed Variational Inference for Bayesian Nonparametrics
This paper presents a methodology for creating streaming, distributed
inference algorithms for Bayesian nonparametric (BNP) models. In the proposed
framework, processing nodes receive a sequence of data minibatches, compute a
variational posterior for each, and make asynchronous streaming updates to a
central model. In contrast to previous algorithms, the proposed framework is
truly streaming, distributed, asynchronous, learning-rate-free, and
truncation-free. The key challenge in developing the framework, arising from
the fact that BNP models do not impose an inherent ordering on their
components, is finding the correspondence between minibatch and central BNP
posterior components before performing each update. To address this, the paper
develops a combinatorial optimization problem over component correspondences,
and provides an efficient solution technique. The paper concludes with an
application of the methodology to the DP mixture model, with experimental
results demonstrating its practical scalability and performance.Comment: This paper was presented at NIPS 2015. Please use the following
BibTeX citation: @inproceedings{Campbell15_NIPS, Author = {Trevor Campbell
and Julian Straub and John W. {Fisher III} and Jonathan P. How}, Title =
{Streaming, Distributed Variational Inference for Bayesian Nonparametrics},
Booktitle = {Advances in Neural Information Processing Systems (NIPS)}, Year
= {2015}
Gas phase absorption of C702+ below 10 K: astronomical implications
The electronic spectrum of the fullerene dication C702+ has been measured in the gas phase at low temperature in a cryogenic radiofrequency ion trap. The spectrum consists of a strong origin band at 7030 Å and two weaker features to higher energy. The bands have FWHMs of 35 Å indicating an excited state lifetime on the order of one-tenth of a picosecond. Absorption cross-section measurements yield (2 ± 1) × 10−15 cm2 at 7030 Å. These results are used to predict the depth of diffuse interstellar bands (DIBs) due to the absorption by C702+. At an assumed column density of 2 × 1012 cm−2 the attenuation of starlight at 7030 Å is around 0.4% and thus the detection of such a shallow and broad interstellar band would be difficult. The electronic spectrum of C602+ shows no absorptions in the visible. Below 4000 Å the spectra of C60, C60+ and C602+ are similar. The large intrinsic FWHM of the features in this region, ~200 Å for the band near 3250 Å, make them unsuitable for DIB detection
Calculated effects of the lateral acceleration derivatives on the dynamic lateral stability of a delta-wing airplane
Factors Affecting Lateral Stability and Controllability
The effects on dynamic lateral stability and controllability of some of the important aerodynamic and mass characteristics are discussed and methods are presented for estimating the various stability parameters to be used in the calculation of the dynamic lateral stability of airplanes with swept and low-aspect-ratio wings
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