Sarah Middle

Inference for Change-Point and Related Processes

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Sarah Middle
Inference for Change-Point and Related Processes

Episodes

Sarah Middle

Inference for Change-Point and Related Processes

An Itunes U podcast

Good podcast? Give it some love!

Rate Podcast

Episodes of Inference for Change-Point and Related Processes

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A primal dual method for inverse problems in MRI with non-linear forward operators

Feb 14th, 2014 29m 32s

Valkonen, T (University of Cambridge)Friday 07 February 2014, 14:30-15:00

Applications of Change-Points Methods in Brain Signal and Image Analysis

Feb 12th, 2014 56m 55s

Ombao, H (University of California, Irvine)Wednesday 05 February 2014, 11:30-12:30

Wavelet-based Bayesian Estimation of Long Memory Models - an Application to fMRI Data

Feb 12th, 2014 58m 36s

Vannucci, M (Rice University)Tuesday 04 February 2014, 14:00-15:00

Detecting copy number variants for rare genetic disorders and non-invasive pre-natal diagnosis

Feb 12th, 2014 59m 38s

Plagnol, V (University College London)Tuesday 04 February 2014, 11:30-12:30

Methods for detecting graph based change points for fMRI and financial data

Feb 12th, 2014 52m 30s

Cribben, I (University of Alberta)Wednesday 05 February 2014, 10:00-11:00

Exact Bayesian inference for change point models with application to genomics

Feb 12th, 2014 54m 19s

Robin, S (INRA - Institut National de la Recherche Agronomique)Monday 03 February 2014, 14:00-15:00

Detection of Genomic Signals by Resequencing

Feb 11th, 2014 1h 1m

Siegmund, D (Stanford University)Monday 03 February 2014, 11:30-12:30

Theory and Inference for a Class of Nonlinear Models with Application to Time Series of Counts.

Feb 5th, 2014 1h 1m

Davis, R (Columbia University)Thursday 30 January 2014, 11:30-12:30

Modeling spatial nonstationarity and inference for exceedances in environmental applications.

Feb 5th, 2014 1h 7m

Craigmile, P (Ohio State University)Tuesday 28 January 2014, 11:30-12:30

Incorporating Geostrophic Wind Information for Improved Space-Time Short-Term Wind Speed Forecasting and Power System Dispatch.

Feb 5th, 2014 1h 4m

Genton, M (King Abdullah University of Science and Technology (KAUST))Wednesday 29 January 2014, 11:30-12:30

Graph-Based Change-Point Detection

Feb 3rd, 2014 1h 9m

Chen, H (University of California, Davis)Tuesday 21 January 2014, 11:30-12:30

Fourier based statistics for irregular spaced spatial data: with an application to testing for spatial stationarity.

Feb 3rd, 2014 1h 1m

Subba Rao , S (Texas A&M University )Friday 24 January 2014, 14:00-15:00

Robust monitoring of CAPM portfolios beta

Feb 3rd, 2014 1h 5m

Husková, M (Charles University, Prague)Wednesday 22 January 2014, 11:30-12:30

Measuring dependence with local Gaussian correlation: Theory and applications.

Feb 3rd, 2014 1h 1m

Tjøstheim, D (Universitetet i Bergen)Thursday 23 January 2014, 11:30-12:30

Statistical Inference for Panel Data

Feb 3rd, 2014 1h 2m

Horvath, L (University of Utah)Friday 24 January 2014, 12:00-13:00

The Volatility of International Migration Flows: Estimating Past Trends in Nordic Countries and Lessons for Forecasting with Uncertainty.

Feb 3rd, 2014 47m 25s

Abel, G (Austrian Academy of Sciences)Tuesday 21 January 2014, 14:00-15:00

Characterizing, predicting and handling rapid and large changes of wind power production.

Jan 28th, 2014 1h 12m

Girard, R (Mines Paris Tech)Monday 27 January 2014, 15:10-16:10

Precision of Disorders Detection

Jan 27th, 2014 26m 7s

Szajowski, K (Wroclaw University of Technology)Wednesday 15 January 2014, 16:30-17:00

An Automated Statistician which learns Bayesian nonparametric models of time series data

Jan 24th, 2014 1h

Ghahramani, Z (University of Cambridge)Thursday 16 January 2014, 14:15-15:00

The group fused Lasso for multiple change-point detection

Jan 24th, 2014 46m 57s

Vert, J-P (Mines ParisTech)Friday 17 January 2014, 09:30-10:15

Quickest Changepoint Detection: Optimality Properties of the Shiryaev-Roberts-Type Procedures

Jan 24th, 2014 44m 23s

Tartakovsky , A (University of Connecticut)Friday 17 January 2014, 10:15-11:00

Bayesian inference in continuous time jump processes

Jan 24th, 2014 44m 32s

Godsill, S (University of Cambridge)Thursday 16 January 2014, 13:30-14:15

Adaptive Spectral Estimation for Nonstationary Time Series

Jan 24th, 2014 39m 12s

Stoffer, D (University of Pittsburgh)Friday 17 January 2014, 11:30-12:15

Computationally Efficient Algorithms for Detecting Changepoints

Jan 24th, 2014 39m 43s

Fearnhead, P (Lancaster University)Thursday 16 January 2014, 09:30-10:00

An algorithm to segment count data using a binomial negative model

Jan 24th, 2014 32m 23s

Rigaill, G (INRA-CNRS-Université d'Evry Val d'Essonne, URGV)Thursday 16 January 2014, 10:00-10:30

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