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Learning a probability distribution from samples drawn from unknown function

I am wanting to learn some probability distribution $p$ from data (using e.g., Kernel Density Estimation, a Normalizing Flow, whatever your favourite machine learning model is). If I had a dataset $D =...
Craig Innes's user avatar
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0 answers
89 views

How to compute the bias of the auto-normalized importance sampling estimator

A preceding post has compared auto-normalized importance sampling with ordinal importance sampling. Beginner readers shall be directed there, but I will remind the readers of just enough elements for ...
Fernando Zhu's user avatar
2 votes
1 answer
263 views

Monte-Carlo integration with importance-sampling

I came across a paper, where (section 3.2) importance sampling is used to estimate an integral. I think I understand what importance sampling is but I don't understand how they got the solution. The ...
harsanyidani's user avatar
1 vote
0 answers
113 views

In the β-TCVAE paper, can someone help with the derivation (S3) in Appendix C.1?

Paper: Isolating Sources of Disentanglement in VAEs I follow as far as, $$\mathbb{E}_{q(z)}[log[q(z)] = \mathbb{E}_{q(z, n)}[\ log\ \mathbb{E}_{n'\sim\ p(n)}[q(z|n')]\ ]$$ Subsequently, I don't ...
S R's user avatar
  • 33
0 votes
1 answer
939 views

Weighted importance sampling (WIS) and Importance sampling (IS)

I am currently reading papers about off-policy evaluation (or counterfactual evaluation) of reinforcement learning policies, including ones about the doubly robust estimator. As in this paper https://...
Hunnam 's user avatar
  • 155
6 votes
1 answer
155 views

About the variance of a weighted sum

What can be said about the variance of the following quantity $$ \frac{1}{n}\sum_{i=1}^n \left(\frac{f(x_i)}{\sum_{j=1}^nf(x_j)}-b\right)g(x_i) ? $$ Here, $b \in [0, 1]$, and the $x_i$s are i.i.d ...
dohmatob's user avatar
  • 538
12 votes
1 answer
1k views

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

I recently started using Pareto smoothed importance sampling leave-one-out cross-validation (PSIS-LOO), described in these papers: Vehtari, A., & Gelman, A. (2015). Pareto smoothed importance ...
lacerbi's user avatar
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