PPT-Variational

data assimilation and forecast error statistics Ross Bannister 11 th July 2011 University of Reading rnbannisterreadingacuk All models are wrong George Box All models are wrong and all observations are inaccurate. Blei Computer Science Department Princeton University chongwjpaisleyblei csprincetonedu Abstract The hierarchical Dirichlet process HDP is a Bayesian nonparametric model that can be used to model mixedmembership data with a poten tially in64257nite Titsias MTITSIAS AUEB GR Department of Informatics Athens University of Economics and Business Greece Miguel L azaroGredilla MIGUEL TSC UC ES Dpt Signal Processing Communications Universidad Carlos III de Madrid Spain Abstract We propose a simple a uclacuk David Newman and Max Welling Bren School of Information and Computer Science University of California Irvine CA 926973425 USA newmanwelling icsuciedu Abstract Latent Dirichlet allocation LDA is a Bayesian network that has recently gained much of Computer Science Tokyo Institute of Technology Japan kuriharamicstitechacjp Max Welling Dept of Computer Science UC Irvine USA wellingicsuciedu Yee Whye Teh Dept of Computer Science National University of Singapore tehywcompnusedusg Abstract Nonp Wangcsoxacuk Department of Computer Science University of Oxford Oxford OX1 3QD United Kingdom PhilBlunsomcsoxacuk Abstract Approximate inference for Bayesian models is dominated by two approaches variational Bayesian inference and Markov Chain Monte . geometrically. Note that x . Now, since x is the unknown function to be found so as to minimize (or maximize) a functional, we want to see what happens to the functional () J x x is indicated . Radar Data Assimilation for 0-12 hour severe weather forecasting. Juanzhen. Sun . National Center for Atmospheric Research. Boulder, Colorado. sunj@ucar.edu. Outline. . Background. - . Motivation . for the NCEP GFS. Tom Hamill, for . Jeff . Whitaker. NOAA Earth System Research Lab, Boulder, CO, USA. jeffrey.s.whitaker@noaa.gov. Daryl Kleist, Dave Parrish and John . Derber. National Centers for Environmental Prediction, Camp Springs, MD, USA. and. . Optimality in nature. Andrej Cherkaev. Department of Mathematics University of Utah. cherk@math.utah.edu. USAG November 2013.. Components of applied math. Optimization. Numerical Methods. Differential equations . DIMENTIONAL SPECTRA . M. VILLA. U.A.M.-I. (México) . and. M. L. SENENT. C.S.I.C. (. Spain. ). Objectives:. We present preliminary results for DME . . 1) DME is an interstellar molecule . Qifeng. Chen. Stanford University. Vladlen. . Koltun. Intel Labs. Optical flow. Motion field between two image frames. Optical flow. Motion field between two image frames. Image 1. Image 2. optical flow. Inference. Dave Moore, UC Berkeley. Advances in Approximate Bayesian Inference, NIPS 2016. Parameter Symmetries. . Model. Symmetry. Matrix factorization. Orthogonal. transforms. Variational. . a. A comparison of hybrid variational data assimilation methods in the Met Office global NWP system Andrew Lorenc 11 th Adjoint Workshop, Aveiro Portugal, July 2018 www.metoffice.gov.uk © Crown Copyright 2018, Met Office Henning Lange, Mario . Bergés. , Zico Kolter. Variational Filtering. Statistical Inference. (Expectation Maximization, Variational Inference). Deep Learning. Dynamical Systems. Variational Filtering.