How Universal approximation theorem works part5(Machine Learning)
A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions(arXiv) Author : Yulong Lu, Jianfeng Lu Abstract : This paper studies the universal approximation property of deep neural networks for representing probability distributions. Given a target distribution π and a source distribution pz both defined on Rd, we…
How Universal approximation theorem works part5(Machine Learning) A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions(arXiv) Author : Yulong Lu, Jianfeng Lu Abstract : This paper studies the universal approximation property of deep neural networks for representing probability distributions. Given a target distribution π and a source distribution pz both defined on Rd, we… deep-learning
Universal approximation theorem work part5Machine Learning Universal Approximation Theorem Deep Neural Networks Expressing Probability DistributionsarXiv Author Yulong Lu Jianfeng Lu Abstract paper study universal approximation property deep neural network representing probability distribution Given target distribution π source distribution pz defined Rd we… deeplearning