cs401r_w2016
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cs401r_w2016 [2016/01/09 22:48] admin |
cs401r_w2016 [2021/06/30 23:42] (current) |
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| [[cs401r_w2016:lab2|Lab 2 - Bayesian concept learning]] | [[cs401r_w2016:lab2|Lab 2 - Bayesian concept learning]] | ||
| - | [[cs401r_w2016:lab4|Lab 3 - Gaussian process regression]] | + | [[cs401r_w2016:lab5|Lab 3 - MNIST with KDE]] |
| - | [[cs401r_w2016:lab5|Lab 4 - MNIST with KDE]] | + | [[cs401r_w2016:lab4|Lab 4 - Gaussian process regression]] |
| - | [[cs401r_w2016:lab13|Lab 5 - Expectation maximization]] | + | [[cs401r_w2016:lab14|Lab 5 - Large-scale Gaussian process regression]] |
| - | [[cs401r_w2016:lab6|Lab 6 - Kalman filter]] | + | [[cs401r_w2016:lab13|Lab 6 - Expectation maximization]] |
| - | [[cs401r_w2016:lab7|Lab 7 - localization with particle filters]] | + | [[cs401r_w2016:lab7|Lab 7 - Kalman filter]] |
| - | [[cs401r_w2016:lab8|Lab 8 - LDA, wikipedia, and Gibbs sampling]] | + | [[cs401r_w2016:lab8|Lab 8 - Localization with particle filters]] |
| - | [[cs401r_w2016:lab9|Lab 9 - improved generative images with MCMC]] | + | [[cs401r_w2016:lab9|Lab 9 - LDA, General Conference, and Gibbs sampling]] |
| - | [[cs401r_w2016:lab10|Lab 10 - Bayesian super resolution]] | + | [[cs401r_w2016:lab10|Lab 10 - Metropolis Hastings and Hamiltonian MCMC]] |
| - | [[cs401r_w2016:lab11|Lab 11 - weather data with BP]] | + | [[cs401r_w2016:lab12|Lab 11 - Recommender system]] |
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| - | [[cs401r_w2016:lab12|Lab 12 - recommender system]] | + | |
| + | [[cs401r_w2016:fp|Final project]] | ||
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| [[cs401r_w2016:lab3|Lab 3 - basic PDF library]] | [[cs401r_w2016:lab3|Lab 3 - basic PDF library]] | ||
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| + | [[cs401r_w2016:lab11|Lab 11 - Bayesian super resolution]] | ||
cs401r_w2016.1452379729.txt.gz · Last modified: 2021/06/30 23:40 (external edit)
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