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Generative model

Known as: Generative statistical model 
In probability and statistics, a generative model is a model for randomly generating observable data values, typically given some hidden parameters… 
Wikipedia

Papers overview

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Highly Cited
2017
Highly Cited
2017
Semantic image inpainting is a challenging task where large missing regions have to be filled based on the available visual data… 
Highly Cited
2016
Highly Cited
2016
This paper introduces WaveNet, a deep neural network for generating raw audio waveforms. The model is fully probabilistic and… 
Highly Cited
2015
Highly Cited
2015
Supervised deep learning has been successfully applied to many recognition problems. Although it can approximate a complex many… 
Highly Cited
2014
Highly Cited
2014
We propose a new framework for estimating generative models via an adversarial process, in which we simultaneously train two… 
Highly Cited
2014
Highly Cited
2014
Generative Adversarial Nets [8] were recently introduced as a novel way to train generative models. In this work we introduce the… 
Highly Cited
2014
Highly Cited
2014
We marry ideas from deep neural networks and approximate Bayesian inference to derive a generalised class of deep, directed… 
Highly Cited
2014
Highly Cited
2014
The ever-increasing size of modern data sets combined with the difficulty of obtaining label information has made semi-supervised… 
Highly Cited
2008
Highly Cited
2008
Formal languages for probabilistic modeling enable re-use, modularity, and descriptive clarity, and can foster generic inference… 
Review
2003
Review
2003
Recently, I became interested in a current debate over whether file size distributions are best modelled by a power law… 
Highly Cited
1997
Highly Cited
1997
In this paper we first propose a new statistical parsing model, which is a generative model of lexicalised context-free grammar…