mlsanityData to 7 Oct 2026

BARMPy: Bayesian Additive Regression Models Python Package

arXiv 2404.04738 ↗First posted 6 Apr 2024stat.CO stat.MLcited by 0

Not on the map. Why?

Abstract (arXiv)

We make Bayesian Additive Regression Networks (BARN) available as a Python package, textttbarmpy, with documentation at urlhttps://dvbuntu.github.io/barmpy/ for general machine learning practitioners. Our object-oriented design is compatible with SciKit-Learn, allowing usage of their tools like cross-validation. To ease learning to use textttbarmpy, we produce a companion tutorial that expands on reference information in the documentation. Any interested user can textttpip install barmpy from the official PyPi repository. textttbarmpy also serves as a baseline Python library for generic Bayesian Additive Regression Models.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 36 references that are in the map. First posted on arXiv 6 Apr 2024.

Builds on

6 of 36 references.

References · 6

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2020NeuralSens: Sensitivity Analysis of Neural Networkscited by 14
  4. 2020Bayesian Additive Regression Trees with Model Treescited by 11
  5. 2022Generalized Bayesian Additive Regression Trees Models: Beyond Conditional Conjugacycited by 8
  6. 2022The Rise of GitHub in Scholarly Publicationscited by 4

Built on by

Not cited yet.