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In GitLab by @vinayak1 on Nov 21, 2017, 11:44
Hi everyone,
So I'm working on generalising how algorithms are imported into the `python_wrapper.py` so that it does not check only for sceua but also a…
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# Rationale
The current implementation for drawing uniformly random numbers in a given range is based on rejection sampling, see
https://github.com/divergencetech/ethier/blob/a0b71a96a51e5a9080e0f0b…
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This module will show the evolution of sampling algorithms showing the ground truth and samples that are accepted/rejected, importance weights and so on.
The idea is to provide a video generation …
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```
Implement a generic infrastructure for handling samplers. Many of the
algorithms to implement rely on a solid sampling infrastructure.
Samplers are basically random number generators which create…
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## Description
Analogous to other distributions, add support for the [inverse Gaussian distribution](https://www.wikiwand.com/en/Inverse_Gaussian_distribution) with a sampling statement and Stan func…
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I have been doing several tests with ABF&ANN + Particle separation as CV, with different number of walkers distributed in different regions of the expected PMF landscape (I have previously got the PMF…
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Hello guys, I wonder if there is a way to train the Actor Critic algorithms in an off-policy manner, as in the paper [Sample Efficient Actor-Critic with Experience Replay](https://arxiv.org/abs/1611.0…
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I'm reading [this master thesis](https://tspace.library.utoronto.ca/bitstream/1807/98008/2/Gao_Jian_201911_MAS_thesis.pdf) (Thompson Sampling with Belief Update for Piece-wiseStationary Multi-armed Ba…
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Add machine learning results
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This issue should address the question on how to solve an inference problem using sampling routines (for example [MCMC](https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo)) in a parallelization fr…