R Observatory: Metrics for LBBNN version 0.1.6

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

LBBNN

0.1.6Package record

Latent Binary Bayesian Neural Networks Using 'torch'

0packages depend

4.2Kdownloads / year

0.0%test coverage

13/13flavors OK

Overview

About

Maintained by Lars Skaaret-LundCRAN page ↗

Latent binary Bayesian neural networks (LBBNNs) are implemented using 'torch', an R interface to the LibTorch backend. Supports mean-field variational inference as well as flexible variational posteriors using normalizing flows. The standard LBBNN implementation follows Hubin and Storvik (2024) doi:10.3390/math12060788, using the local reparametrization trick as in Skaaret-Lund et al. (2024) https://openreview.net/pdf?id=d6kqUKzG3V. Input-skip connections are also supported, as described in Høyheim et al. (2025) doi:10.48550/arXiv.2503.10496.

Changes in 0.1.6

Added more vignettes, built pkgdown website.
More robust testing.
Bug fix in conv2d layer.
Small changes to make training on gpu more efficient.
Added possibility to turn off printing to console during training.
Utility functions work with standard LBBNN architecture without input-skip.
predict() and validate_lbbnn() no longer change the model object.
fixed bug that compute_paths() was not being called for LBBNN models.
added initialization keywords such as 'dense' or 'balanced' for inclusion probabilities.
added possibility for different weight initializations.

From NEWS.md in the release

Install

R (CRAN)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("LBBNN", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-lbbnn

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-LBBNN

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-LBBNN

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 2.2 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.1.6

READMEYes · 489 wordsVignettesYes · 5 · dynamicNEWSYes · 67% structured · mentions 0.1.6Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 33 (10 internal)includes a package overview page
Examples that run: 0%12 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 46%
Documented parameters: 100%
Return-value docs: 92%
Help pages citing references: 0%

Vignettes (5)

How these are measured

Downloads

4.2K

CRAN downloads in the past year

Rank #16,969 · ~12/day · ~352/mo

Releases R versions

Daily download trend is not available in this view yet.

29630 days

73590 days

4.2K1 year

Compare downloads with other packages →

Also on91 r2u6 autocran

How downloads are counted

Dependencies

Declared dependencies

9 external dependencies (excludes base and recommended)

Installing LBBNN adds 37 packages (21 with compiled code, 36 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, igraph 4.8 MB.

Depends (1)

R >= 3.5

Imports (5)

ggplot2 torch igraph coro svglite

LinkingTo (0)

none

Suggests (4)

testthat knitr rmarkdown torchvision

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (3)

Lars Skaaret-Lund

Author, Maintainer since 0.1.1 (2025)

Aliaksandr Hubin

Author

Eirik Høyheim

Author

Releases (6)

Pick two releases to compare their code metrics.

0.1.6Latest
record
2026-06-30 · current release · diff ↗ ·
added 1 export
resolve_device
R
R 4.6.0 released · 2026-04-24
0.1.5
record
2026-04-23 · diff ↗ ·
added 1 export
torch_available
0.1.4
record
2026-01-12 · diff ↗
0.1.3
record
2026-01-07 · diff ↗ ·
removed 10 exports
Custom_activation, FLOW, LBBNN_Conv2d, LBBNN_Linear, LBBNN_Net, LBBNN_plot, RNVP_layer, plot_local_explanations_gradient, train_LBBNN, validate_LBBNN

added 8 exports
custom_activation, lbbnn_conv2d, lbbnn_linear, lbbnn_net, normalizing_flow, rnvp_layer, train_lbbnn, validate_lbbnn
0.1.2
record
2025-12-10 · diff ↗
0.1.1
record
2025-12-01
R
R 4.5.0 released · 2025-04-11

Package metadata

First published: 2025-12-01
Total releases: 6 / 1 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 3.5
Bundled data: 51 KB / 2 files
Download size: 557 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("LBBNN")

Format

Skaaret-Lund, L., Hubin, A., & Høyheim, E. (2026). LBBNN: Latent Binary Bayesian Neural Networks Using 'torch' (Version 0.1.6) [Computer software]. https://doi.org/10.32614/CRAN.package.LBBNN

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for LBBNN version 0.1.6 [Data set]. HJJB, LLC. Data release v2026-10-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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