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#hamiltonianmontecarlo#mcmc#bayesianinference

Efficient Bayesian inference with Hamiltonian Monte Carlo -- Michael Betancourt (Part 1)

MLSS Iceland 2014

1.8K subscribers • 1 video on Hallway

YouTube
  • Recommended by 3 people: 3 on Hacker News.
  • A classic. People kept recommending it from 2017 to 2024.
  • Presented by Michael Betancourt, statistician
  • May be out of date. Uploaded 11 years ago, in an area where tools change fast.

Advanced. Deep dive for people who know the field.

47K views11 years ago3 recommendations

AI and machine learningComputer scienceMath for machine learningClassic machine learningAlgorithms

Michael Betancourt explains the concepts, motivations, and challenges of Markov chain Monte Carlo and Hamiltonian Monte Carlo in high-dimensional spaces.

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Why it's here

3 people recommend this

What people say. Recommended as a fantastic primer on MCMC and high-dimensional probability distributions.

leecarraheron Hacker News • Recommends

On “Markov chain Monte Carlo without the bullshit (2015)”

Recently watched this on Hamiltonian Monte Carlo, and it was a fantastic primer on the basic concepts and motivations of mcmc, and later hmc link to this video
View on Hacker News

srs70187on Hacker News • Recommends

On “Gaussian Distributions Are Soap Bubbles”

This is an interesting take and kudos to the author for relaying a helpful way to think about high dimensional distributions. I really like and often come back to this talk by Michael Betancourt where the theme is quite similar: link to this video
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euW3EeBeon Hacker News • Recommends

On “Gradient descent visualization”

…d guess that gradient descent would get stuck in these corners and have a hard time getting out. Some links related to this: - Spikey Spheres: link - Thinking outside the 10-dimensional box - 3blue1brown: link - This is a fairly long talk about HMC, but it does talk about some problems that come up when sampling high-dimensional distributions: link to this video…
View on Hacker News