2016-04-28-machine-learning-with-gaussian-processes.md

abstract	author	categories	day	demo	errata	extras	key	layout	month	pdf	ppt	published	section	title	venue	year
Gaussian processes (GPs) provide a principled probabilistic approach to prior probability distributions for functions. In this talk we will give an overview of some uses of GPs and their extensions. In particular we will introduce mechanistic models alongside GPs and also use GPs within a structured framework of latent variable models.	family given gscholar institute twitter url Lawrence Neil D. r3SJcvoAAAAJ University of Sheffield lawrennd http://inverseprobability.com	Lawrence-amazon16	28	demo_2016_04_28_amazon.m			Lawrence-amazon16	talk	4	2016-04-28-MLGPsAmazon.pdf	2016-04-28-MLGPsAmazon.pptx	2016-04-28	pre	Machine Learning with Gaussian Processes	Amazon Machine Learning Conference, Seattle	2016