'Data augmentation' presentation slideshows

Introduction to MCMC methods, the Gibbs Sampler, and Data Augmentation

Introduction to MCMC methods, the Gibbs Sampler, and Data Augmentation. Simulation Methods. problem: Bayes theorem allows us to write down unnormalized density which proportional to the posterior for virtually any model, construct a simulator dim( ? ) > 100 Solutions:

760 views • 61 slides

Handling Missing Data

Handling Missing Data. Estie Hudes Tor Neilands UCSF Center for AIDS Prevention Studies Part 2 January 18, 2013. Contents. 1. Summary of Part 1 2. EM Algorithm 3. Multiple Imputation (MI) for normal data 4. Multiple Imputation (MI) for mixed data 5. Steps in multiple imputation

520 views • 37 slides

Structural Estimation of the Effect of Out-of-Stocks

442 views • 36 slides

EFFECTIVE PREDICTIVE MODELING- DATA,ANALYTICS AND PRACTICE MANAGEMENT

EFFECTIVE PREDICTIVE MODELING- DATA,ANALYTICS AND PRACTICE MANAGEMENT. Richard A. Derrig Ph.D. OPAL Consulting LLC Karthik Balakrishnan Ph.D. ISO Innovative Analytics CANE Meeting Southbridge, MA

306 views • 30 slides

Towards a VQA Suite: Architecture Tweaks, Learning Rate Schedules, and Ensembling

Towards a VQA Suite: Architecture Tweaks, Learning Rate Schedules, and Ensembling. Tina Jiang*, Vivek Natarajan*, Xinlei Chen*, Marcus Rohrbach , Dhruv Batra, Devi Parikh. June 18 th, 2018. VQA architecture. Question Encoding. Multimodal Fusion. Classifier.

966 views • 22 slides

Transforming Healthcare at GTC Silicon Valley

The GPU Technology Conference (GTC) brings together the leading minds in AI and healthcare that are driving advances in the industry - from top radiology departments and medical research institutions to the hottest startups from around the world. Can't miss panels and trainings at GTC Silicon Valley

201 views • 12 slides

SEQUENTIAL IMPUTATIONS AND BAYESIAN MISSING DATA PROBLEMS AUGUSTING KONG, JUN LIU WING HUNG WONG

221 views • 9 slides