Final term project for Bayesian Machine Learning Lecture (XAI-623)

JeongEun Park

Last update: Jan 18, 2022

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Overview

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Final Term Project For Bayesian Machine Learning Lecture (XAI-623)

Youtube Link

The presentation is given in YoutubeLink

Problem Formulation

Dirty MNIST

Active learning on MNIST: Ambiguous MNIST = 1:60

which is same with DDU paper.

OOD MNIST

Active learning on MNIST: Ambiguous MNIST : EMNIST = 1:60:1

Method

use MLN + Feature Density Traning process of MLN is same as paper and implementation. Estimation of feature density is done by modeling GMM with EM algorithm, implemented here

Expriment Results

Dirty MNIST

OOD MNIST

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Owner

JeongEun Park

Interested in artificial intelligence and robotics

GitHub

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Final term project for Bayesian Machine Learning Lecture (XAI-623)

Related tags

Overview

Mixquality_AL

Youtube Link

Problem Formulation

Method

Expriment Results

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