由图灵奖获得者Pearl开发出来。如果用一个词来形容概率图模型(Probabilistic Graphical Model)的话,那就是“优雅”。对于一个实际问题,我们希望能够挖掘隐含在数据中的知识。概率图模型构建了这样一幅图,用观测结点表示观测到的数据,用隐含结点表示潜在的知识,用边来描述知识与数据的相互关系,最后基于这样的关系图获得...
变分自编码器(Variational Autoencoder/VAE)使得我们可以在概率图形模型(probabilistic graphical model)的框架下将这个问题形式化,在此框架下我们可以最大化数据的对数似然值的下界。在本文中,我们将介绍一种最新开发的架构,即对抗自编码器(Adversarial Autoencoder),它由 VAE 启发,但它在数据到潜在维度的映射方式中(如...
主成分分析(principal component analysis):用少量的参数来准确地捕捉数据的线性相关属性 因果关系(causality)和概率图模型(probabilistic graphical models):根据经验数据发现属性之间的关系 生成对抗性网络(generative adversarial networks):通过两个神经网络相互博弈的方式进行学习,生成数据 与环境互动 离线学习(offline learn...
Variational Autoencoders (VAEs) allow us to formalize this problem in the framework of probabilistic graphical models where we are maximizing a lower bound on the log likelihood of the data. In this post we will look at a recently developed architecture, Adversarial Autoencoders, which are insp...
•因果关系(causality)和概率图模型(probabilisticgraphicalmodels)问题:我们能否描述观察到的 许多数据的根本原因?例如,如果我们有关于房价、污染、犯罪、地理位置、教育和⼯资的⼈口统计数 据,我们能否简单地根据经验数据发现它们之间的关系? •⽣成对抗性⽹络(generativeadversarialnetworks):为我们提供⼀种合...
Optionally, a fully-connected probabilistic graphical model, namely, CRF, can be applied to refine the final predictions. On the test set of PASCAL VOC, the model achieves 79.7% with CRFs and 76.4% without CRFs of mean intersection-over-union. For more details on the underlying model please...
Build a Logistic Regression Model in PyTorch This project aims to build a logistic regression model in PyTorch from scratch. Logistic regression is a probabilistic model that models the probabilities of discrete outcomes given the input variables. The end goal of the project is to: ...
Integrated GradientsAxiomatic Attribution for Deep Networks GNNExplainerGNNExplainer: Generating Explanations for Graph Neural Networks PGExaplinerParameterized Explainer for Graph Neural Network PGM-ExaplinerPGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks ...
It is initially developed by Facebook artificial-intelligence research group, and Ubers Pyro software for probabilistic programming which is built on it. Originally, PyTorch was developed by Hugh Perkins as a Python wrapper for the LusJIT based on Torch framework. There are two PyTorch variants. ...
变分自编码器(Variational Autoencoder/VAE)使得我们可以在概率图形模型(probabilistic graphical model)的框架下将这个问题形式化,在此框架下我们可以最大化数据的对数似然值的下界。在本文中,我们将介绍一种最新开发的架构,即对抗自编码器(Adversarial Autoencoder),它由 VAE 启发,但它在数据到潜在维度的映射方式中(如...