PPT-A variational

formulation for higher order macroscopic traffic flow models of the GSOM family JP Lebacque UPEIFSTTARGRETTIA Le Descartes 2 2 rue de la Butte Verte F93166 NoisyleGrand France Jeanpatricklebacqueifsttarfr. Gershman sjgershmprincetonedu Department of Psychology Princeton University Green Hall Princeton NJ 08540 USA Matthew D Ho64256man mdhoffmacsprincetonedu Department of Statistics Columbia University New York NY 10027 USA David M Blei bleics 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 1 A New Beginning 113 112 De nition of Bar Member 113 113 Variational Formulation 114 1131 The Total Potential Energy Functional 114 1132 Admissible Variations 116 1133 The Minimum Total Potential Energy Principle 116 1134 TPE Discretization 117 T Rockafellar 57th Meeting of the Indian Mathematical Society Aligarh December 2730 1991 Abstract The study of problems of maximization or minimization subject to constraints has been a fertile 64257eld for the development of mathematical analysis uclacuk Kenichi Kurihara Dept of Computer Science Tokyo Institute of Technology kuriharamicstitechacjp Max Welling ICS UC Irvine wellingicsuciedu Abstract A wide variety of Dirichletmultinomial topic models have found interesting ap plications in rec . Bayesian. . Inference. I:. Pattern . Recognition . and. Machine Learning. Chapter 10. Falk. . LIEDER . December. 2 2010.  . Structural. . Approximations. Statistical . Inference. Introduction. P. Lewis. What is Data Assimilation?. Optimal merging of models and data. Models. Expression of current understanding about process. E.g. terrestrial C model. Data. Observations. E.g. EO. . Some basic stats. data assimilation. and forecast error statistics. Ross Bannister, 11. th. July 2011. University of Reading, r.n.bannister@reading.ac.uk. “All models are wrong …” . (George Box). “All models are wrong and all observations are inaccurate”. 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 . 1. , Olaf Konrad. 2. , Heinz-Otto Peitgen. 1. Fast and Smooth Interactive Segmentation of Medical Images Using Variational Interpolation. 1. . Fraunhofer. MEVIS, Germany. 2. . MeVis. Medical Solutions, Germany. EGU 2012, Vienna. Michail Vrettas. 1. , Dan Cornford. 1. , Manfred Opper. 2. 1. NCRG, Computer Science, Aston University, UK. 2. Technical University of Berlin, Germany. Why do data assimilation?. Aim of data assimilation is to estimate the posterior distribution of the state of a dynamical model (X) given observations (Y). . Autoencoders. Theory and Extensions. Xiao Yang. Deep learning Journal Club. March 29. Variational. Inference. Use a simple distribution to approximate a complex distribution. Variational. parameter:. 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. Henning Lange, Mario . Bergés. , Zico Kolter. Variational Filtering. Statistical Inference. (Expectation Maximization, Variational Inference). Deep Learning. Dynamical Systems. Variational Filtering.