pyro-ppl/pyro

Implement Nonparametric Hamiltonian Monte Carlo

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#2,903 opened on 2021年7月15日

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説明

This issue proposes adding an implementation of nonparametric Hamiltonian Monte Carlo, a modified version of HMC that provably correctly handles models with stochastic control flow, unlike vanilla HMC.

@fzaiser (one of the paper's authors) has open-sourced a PyTorch reference implementation, and turning this into a Pyro inference algorithm would be a great project for contributors with some preexisting interest in and knowledge of the line of research (on extensions of gradient-based approximate inference algorithms to discontinuous models) embodied in the paper.

Some questions for discussion:

  1. What extra information about the model is necessary to support the algorithms used in the paper's experiments?
  2. Can this information be extracted automatically, or would it require additional user-supplied annotations?
  3. Would it make more sense to implement this functionality in a new MCMC kernel or to modify our existing HMC kernels?
  4. Would NumPyro be a better substrate for this algorithm since Jax does not compile away control flow?

コントリビューターガイド

技術スタック
pythonpytorch
領域
machine learningai
Issue 種別
feature
難度新しい貢献者にとっての実装難度です。1 は非常に小さな変更、5 は専門的な作業です。
5
推定時間経験ある貢献者が調査、実装、テスト、pull request 準備にかけるおおよその時間範囲です。
over 1 week
活動状況Issue が今どれだけ取り組みやすいかを示します。新しい、活発、古い、ブロック中、またはメンテナー入力待ちなどです。
stale
明確さ期待される変更、受け入れ条件、次の手順がどれだけ明確かを示します。
unclear
前提条件
Knowledge of Hamiltonian Monte CarloFamiliarity with PyTorchUnderstanding of probabilistic programming
初心者向け度初回貢献者にどれだけ取り組みやすいかを 1-100 で推定したスコアです。
10
調査方針
Research the paper referenced (arxiv.org/abs/2106.10238) and the PyTorch reference implementation at github.com/fzaiser/nonparametric hmc. Investigate how to adapt the algorithm to Pyro's existing MCMC kernel structure. The issue raises several open questions: determining necessary model information, automation vs. user annotations, whether to implement as new kernel or modify existing HMC kernels, and whether NumPyro (with JAX) would be a better substrate due to JAX's handling of control flow. Consider exploring these questions through prototyping and consulting Pyro's source code for examples of existing inference algorithms.