From 12933309a41dc96deaa76cf3dd342e5e194824bb Mon Sep 17 00:00:00 2001 From: Meesum Qazalbash Date: Sat, 21 Sep 2024 21:24:02 +0500 Subject: [PATCH] GWKokab a parameter estimation package in domain of astrophysics (#68) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * gwkokab a parameter estimation for models in astrophysics * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix 2 dead links https://pnas.org/doi/10.1073/pnas.2109420119 β†’ Status: 403 [βœ–] https://flowtorch.ai β†’ Status: 404 * add https://doi.org/10.1073/pnas.2109420119 to .github/workflows/link-check-config.json ignorePatterns * revert to numbered ToC --------- Co-authored-by: Janosh Riebesell --- .github/workflows/link-check-config.json | 4 +++ .pre-commit-config.yaml | 2 +- data/packages.yml | 13 ++++++-- data/publications.yml | 2 +- readme.md | 40 ++++++++++++++---------- 5 files changed, 40 insertions(+), 21 deletions(-) diff --git a/.github/workflows/link-check-config.json b/.github/workflows/link-check-config.json index aa8faf4..bf78c79 100644 --- a/.github/workflows/link-check-config.json +++ b/.github/workflows/link-check-config.json @@ -5,6 +5,10 @@ "pattern": "^#", "comment": "ignore links starting with a dash (those in the readme's ToC)" }, + { + "pattern": "https://doi.org/10.1073/pnas.2109420119", + "comment": "status 403 in CI but works in browser" + }, { "pattern": "^https://twitter.com", "comment": "Twitter seems to block bot requests, getting a lot of 404s" diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 1dfb094..411b9a5 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -7,7 +7,7 @@ default_install_hook_types: [pre-commit, commit-msg] repos: - repo: https://github.com/astral-sh/ruff-pre-commit - rev: v0.4.10 + rev: v0.6.6 hooks: - id: ruff args: diff --git a/data/packages.yml b/data/packages.yml index c213f52..504269b 100644 --- a/data/packages.yml +++ b/data/packages.yml @@ -20,8 +20,7 @@ authors: Facebook / Meta authors_url: https://opensource.fb.com lang: PyTorch - description: | - [FlowTorch Docs](https://flowtorch.ai) is a PyTorch library for learning and sampling from complex probability distributions using a class of methods called Normalizing Flows. + description: FlowTorch is a PyTorch library for learning and sampling from complex probability distributions using Normalizing Flows. - title: TensorFlow Probability date: 2018-06-22 @@ -122,3 +121,13 @@ lang: JAX docs: https://flowmc.readthedocs.io/en/main/ description: Normalizing-flow enhanced sampling package for probabilistic inference + +- title: GWKokab + date: 2024-07-05 + date_added: 2024-09-21 + last_updated: 2024-09-21 + url: https://github.com/gwkokab/gwkokab + authors: Meesum Qazalbash, Muhammad Zeeshan, Richard O'Shaughnessy + lang: JAX + docs: https://gwkokab.readthedocs.io + description: A JAX-based gravitational-wave population inference toolkit for parametric models diff --git a/data/publications.yml b/data/publications.yml index 6a6888a..8d7d427 100644 --- a/data/publications.yml +++ b/data/publications.yml @@ -399,7 +399,7 @@ description: Normalizing flows have potential in Bayesian statistics as a complementary or alternative method to MCMC for sampling posteriors. However, their training via reverse KL divergence may be inadequate for complex posteriors. This research proposes a new training approach utilizing direct KL divergence, which involves augmenting a local MCMC algorithm with a normalizing flow to enhance mixing rate and utilizing the resulting samples to train the flow. This method requires minimal prior knowledge of the posterior and can be applied for model validation and evidence estimation, offering a promising strategy for efficient posterior sampling. - title: Adaptive Monte Carlo augmented with normalizing flows - url: https://pnas.org/doi/10.1073/pnas.2109420119 + url: https://doi.org/10.1073/pnas.2109420119 date: 2022-03-02 authors: Marylou GabriΓ©, Grant M. Rotskoff, Eric Vanden-Eijnden description: Markov Chain Monte Carlo (MCMC) algorithms struggle with sampling from high-dimensional, multimodal distributions, requiring extensive computational effort or specialized importance sampling strategies. To address this, an adaptive MCMC approach is proposed, combining local updates with nonlocal transitions via normalizing flows. This method blends standard transition kernels with generative model moves, adapting the generative model using generated data to improve sampling efficiency. Theoretical analysis and numerical experiments demonstrate the algorithm's ability to equilibrate quickly between metastable modes, sampling effectively across large free energy barriers and achieving significant accelerations over traditional MCMC methods. diff --git a/readme.md b/readme.md index 1732cf4..23c234c 100644 --- a/readme.md +++ b/readme.md @@ -26,20 +26,21 @@ A list of awesome resources for understanding and applying normalizing flows (NF ## Contents  Table of Contents -1. [πŸ“ Publications](#-publications-60) -1. [πŸ› οΈ Applications](#️-applications-8) -1. [πŸ“Ί Videos](#-videos-8) -1. [πŸ“¦ Packages](#-packages-14) - 1. [PyTorch  PyTorch Packages](#-pytorch-packages) - 1. [TensorFlow  TensorFlow Packages](#-tensorflow-packages) - 1. [JAX  JAX Packages](#-jax-packages) - 1. [Julia  Julia Packages](#-julia-packages) -1. [πŸ§‘β€πŸ’» Repos](#-repos-18) - 1. [PyTorch  PyTorch Repos](#-pytorch-repos) - 1. [JAX  JAX Repos](#-jax-repos) - 1. [TensorFlow  TensorFlow Repos](#-tensorflow-repos) - 1. [Other  Other Repos](#-other-repos) -1. [🌐 Blog Posts](#-blog-posts-5) +1. [Table of Contents](#-table-of-contents) +1. [πŸ“ Publications (60)](#-publications-60) +1. [πŸ› οΈ Applications (8)](#️-applications-8) +1. [πŸ“Ί Videos (8)](#-videos-8) +1. [πŸ“¦ Packages (15)](#-packages-15) + 1. [PyTorch Packages](#-pytorch-packages) + 1. [TensorFlow Packages](#-tensorflow-packages) + 1. [JAX Packages](#-jax-packages) + 1. [Julia Packages](#-julia-packages) +1. [πŸ§‘β€πŸ’» Repos (18)](#-repos-18) + 1. [PyTorch Repos](#-pytorch-repos) + 1. [TensorFlow Repos](#-tensorflow-repos) + 1. [JAX Repos](#-jax-repos) + 1. [Other Repos](#-other-repos) +1. [🌐 Blog Posts (5)](#-blog-posts-5) 1. [🚧 Contributing](#-contributing)
@@ -64,7 +65,7 @@ A list of awesome resources for understanding and applying normalizing flows (NF 1. 2022-05-16 - [Multi-scale Attention Flow for Probabilistic Time Series Forecasting](https://arxiv.org/abs/2205.07493) by Feng, Xu et al.
Proposes a novel non-autoregressive deep learning model, called Multi-scale Attention Normalizing Flow(MANF), where one integrates multi-scale attention and relative position information and the multivariate data distribution is represented by the conditioned normalizing flow. -1. 2022-03-02 - [Adaptive Monte Carlo augmented with normalizing flows](https://pnas.org/doi/10.1073/pnas.2109420119) by GabriΓ©, Rotskoff et al.
+1. 2022-03-02 - [Adaptive Monte Carlo augmented with normalizing flows](https://doi.org/10.1073/pnas.2109420119) by GabriΓ©, Rotskoff et al.
Markov Chain Monte Carlo (MCMC) algorithms struggle with sampling from high-dimensional, multimodal distributions, requiring extensive computational effort or specialized importance sampling strategies. To address this, an adaptive MCMC approach is proposed, combining local updates with nonlocal transitions via normalizing flows. This method blends standard transition kernels with generative model moves, adapting the generative model using generated data to improve sampling efficiency. Theoretical analysis and numerical experiments demonstrate the algorithm's ability to equilibrate quickly between metastable modes, sampling effectively across large free energy barriers and achieving significant accelerations over traditional MCMC methods. [[Code](https://zenodo.org/records/4783701#.Yfv53urMJD8)] 1. 2022-01-14 - [E(n) Equivariant Normalizing Flows](https://arxiv.org/abs/2105.09016) by Satorras, Hoogeboom et al.
@@ -307,7 +308,7 @@ A list of awesome resources for understanding and applying normalizing flows (NF
-## πŸ“¦ Packages (14) +## πŸ“¦ Packages (15)
@@ -328,7 +329,7 @@ Zuko is used in [LAMPE](https://github.com/francois-rozet/lampe) to enable Likel 1. 2020-12-07 - [flowtorch](https://github.com/facebookincubator/flowtorch) by [Facebook / Meta](https://opensource.fb.com)   GitHub repo stars
- [FlowTorch Docs](https://flowtorch.ai) is a PyTorch library for learning and sampling from complex probability distributions using a class of methods called Normalizing Flows. + FlowTorch is a PyTorch library for learning and sampling from complex probability distributions using Normalizing Flows. 1. 2020-02-09 - [nflows](https://github.com/bayesiains/nflows) by [Bayesiains](https://homepages.inf.ed.ac.uk/imurray2/group)   @@ -358,6 +359,11 @@ Zuko is used in [LAMPE](https://github.com/francois-rozet/lampe) to enable Likel ### JAX  JAX Packages +1. 2024-07-05 - [GWKokab](https://github.com/gwkokab/gwkokab) by Meesum Qazalbash, Muhammad Zeeshan et al. +  +GitHub repo stars
+ A JAX-based gravitational-wave population inference toolkit for parametric models [[Docs](https://gwkokab.readthedocs.io)] + 1. 2022-06-17 - [flowMC](https://github.com/kazewong/flowMC) by [Kaze Wong](https://www.kaze-wong.com/)   GitHub repo stars