PPT-The Variational Version of the Local Analysis and Predictio

Steve Albers Yuanfu Xie Hongli Jiang Dan Birkenheuer Isidora Jankov and Zoltan Toth ESRLGSD WRF Workshop June 26 th 2013 Updated 62 5 2013 1 81 0UTC Presentation Outline. 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 Borwein Abstract Modern nonsmooth analysis is now roughly thirty64257ve years old In this paper I shall attempt to analyse brie64258y where the subject stands today where it should be going and what it will take to get there In summary the conclusio 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 . Bayesian. . Inference. I:. Pattern . Recognition . and. Machine Learning. Chapter 10. Falk. . LIEDER . December. 2 2010.  . Structural. . Approximations. Statistical . Inference. Introduction. . 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 . 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”. How do you share code?. Discussion. How we share code. Working in a team, you need to share code. How?. Email attachments?. Sneakernet. ?. What if two people edit the same file at the same time?. Google Docs? . 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. . 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:. Discussion. How we share code. Working in a . team, . you need to share code. How?. Email attachments?. Sneakernet. ?. What if two people edit the same file at the same time?. Google Docs? . Dropbox. Inference. Dave Moore, UC Berkeley. Advances in Approximate Bayesian Inference, NIPS 2016. Parameter Symmetries. . Model. Symmetry. Matrix factorization. Orthogonal. transforms. Variational. . a. -- Evaluating its Analysis . and Forecast. Hongli Jiang, Yuanfu Xie, Steve Albers, Zoltan Toth. NOAA Earth System Research Laboratory Global System Division . Forecast Application Branch. . What is . -- Evaluating its Analysis . and Forecast. Hongli Jiang, Yuanfu Xie, Steve Albers, Zoltan Toth. NOAA Earth System Research Laboratory Global System Division . Forecast Application Branch. . What is . Henning Lange, Mario . Bergés. , Zico Kolter. Variational Filtering. Statistical Inference. (Expectation Maximization, Variational Inference). Deep Learning. Dynamical Systems. Variational Filtering.