User lacerbi

50 votes

Optimization when Cost Function Slow to Evaluate

answered Feb 1, 2016 at 0:20

29 votes

Accepted

Can Machine Learning or Deep Learning algorithms be utilised to "improve" the sampling process of a MCMC technique?

answered Jul 18, 2016 at 17:01

26 votes

Accepted

When are genetic algorithms a good choice for optimization?

answered Dec 3, 2016 at 21:09

20 votes

Accepted

Covariance functions or kernels - what exactly are they?

answered Aug 6, 2016 at 13:08

15 votes

Why should I be Bayesian when my model is wrong?

answered Apr 21, 2017 at 10:30

12 votes

MCMC convergence

answered Mar 10, 2017 at 23:40

12 votes

Best way to evaluate PDF estimation methods

answered Jul 1, 2016 at 8:13

12 votes

Accepted

When (and why) do Bayesians reject valid Bayesian methods?

answered Aug 21, 2016 at 22:20

10 votes

Optimization of stochastic computer models

answered Apr 9, 2016 at 14:10

10 votes

Accepted

Preventing Pareto smoothed importance sampling (PSIS-LOO) from failing

answered Mar 7, 2016 at 13:02

10 votes

Accepted

Log marginal likelihood for Gaussian Process

answered May 17, 2017 at 10:45

8 votes

Accepted

Hamiltonian/Hybrid MCMC 'mass matrix' terminology

answered Aug 10, 2016 at 4:16

7 votes

Accepted

Performance benchmarks for MCMC

answered Apr 4, 2016 at 22:28

7 votes

Accepted

What optimization (maximization/minimization) methods exist contours with lots of kinks?

answered Feb 17, 2016 at 4:20

6 votes

Advantages of Evolutionary Algorithms vs. Gradient Based Optimization

answered Jan 18, 2022 at 9:30

5 votes

Accepted

Marginalization of GP regression hyperparameters with Laplace approximation

answered Sep 23, 2015 at 1:31

5 votes

Accepted

practical implementation detail of Bayesian Optimization

answered Mar 1, 2016 at 5:44

4 votes

What is the equivalent for cdfs of MCMC for pdfs?

answered May 10, 2016 at 14:51

3 votes

Accepted

Objective function of a Genetic Algorithm

answered Dec 2, 2016 at 2:06

2 votes

How to prove this Gaussian Mixture inequality? (Fitting/Overfitting)

answered Jun 18, 2016 at 13:29

2 votes

Accepted

Fit a function f on dataset X such that f(X) fits a histogram

answered Mar 1, 2016 at 0:12

2 votes

Accepted

State-of-the-art sampling methods for different information about target density

answered Feb 12, 2016 at 17:49

2 votes

Accepted

Computing joint entropy from marginal distributions

answered Jul 6, 2018 at 13:04

1 vote

Accepted

cross-validation and over-fitting

answered Mar 14, 2016 at 17:41

1 vote

Gaussian process with boundaries on unobserved variables

answered May 13, 2016 at 13:28

0 votes

Converting random 6-faced dice results to decimal base

answered Sep 9, 2020 at 12:11

Stack Exchange Network

26 Answers

Optimization when Cost Function Slow to Evaluate

Can Machine Learning or Deep Learning algorithms be utilised to "improve" the sampling process of a MCMC technique?

When are genetic algorithms a good choice for optimization?

Covariance functions or kernels - what exactly are they?

Why should I be Bayesian when my model is wrong?

MCMC convergence

Best way to evaluate PDF estimation methods

When (and why) do Bayesians reject valid Bayesian methods?

Optimization of stochastic computer models

Preventing Pareto smoothed importance sampling (PSIS-LOO) from failing

Log marginal likelihood for Gaussian Process

Hamiltonian/Hybrid MCMC 'mass matrix' terminology

Performance benchmarks for MCMC

What optimization (maximization/minimization) methods exist contours with lots of kinks?

Advantages of Evolutionary Algorithms vs. Gradient Based Optimization

Marginalization of GP regression hyperparameters with Laplace approximation

practical implementation detail of Bayesian Optimization

What is the equivalent for cdfs of MCMC for pdfs?

Objective function of a Genetic Algorithm

How to prove this Gaussian Mixture inequality? (Fitting/Overfitting)

Fit a function f on dataset X such that f(X) fits a histogram

State-of-the-art sampling methods for different information about target density

Computing joint entropy from marginal distributions

cross-validation and over-fitting

Gaussian process with boundaries on unobserved variables

Converting random 6-faced dice results to decimal base