Data

Tools

Indexes

Applications

Experiments

Open Source Science

mbi

A library providing general-purpose tools for estimating discrete distributions from noisy observations of their marginals.

https://github.com/ryan112358/mbi

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 3 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (6.0%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

A library providing general-purpose tools for estimating discrete distributions from noisy observations of their marginals.

Basic Info
Statistics
  • Stars: 103
  • Watchers: 2
  • Forks: 47
  • Open Issues: 5
  • Releases: 0
Created almost 7 years ago · Last pushed 7 months ago
Metadata Files
Readme Contributing License Citation

README.md

MBI: Marginal-Based Estimation and Inference

(with applications to differential privacy)

drawing

DOI Continuous integration Documentation Status

Metrics for ryan112358/mbi repository

Documentation can be found at https://private-pgm.readthedocs.io/en/latest/!

Owner

  • Name: Ryan McKenna
  • Login: ryan112358
  • Kind: user

PhD student at UMass Amherst.

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it using these metadata, as well as the associated publication in the Journal of Privacy and Confidentiality."
abstract: "Private-PGM is a post-processing method that is used to estimate a high-dimensional data distribution from noisy measurements of its marginals. "
authors: 
- family-names: "McKenna"
  given-names: "Ryan"
  affiliation: "College of Information and Computer Sciences, The University of Massachusets, Amherst, MA"
- family-names: "Miklau"
  given-names: "Gerome"
  affiliation: "College of Information and Computer Sciences, The University of Massachusets, Amherst, MA"
- family-names: "Sheldon"
  given-names: "Daniel"
  affiliation: "College of Information and Computer Sciences, The University of Massachusets, Amherst, MA"
title: "Private-PGM"
version: "v2021-10-04-jpc"
date-released: 2021-10-04
license: "Apache-2.0"
url: "https://github.com/journalprivacyconfidentiality/private-pgm-jpc-778/tree/v2021-10-04-jpc"

GitHub Events

Total
  • Push event: 4
  • Pull request event: 3
  • Pull request review event: 9
  • Pull request review comment event: 10
  • Fork event: 1
  • Create event: 4
Last Year
  • Push event: 4
  • Pull request event: 3
  • Pull request review event: 9
  • Pull request review comment event: 10
  • Fork event: 1
  • Create event: 4

Packages

  • Total packages: 1
  • Total downloads: unknown
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
pypi.org: mbi

Marginal-based estimation and inference (with applications to differential privacy)

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 8.7%
Average: 28.9%
Dependent repos count: 49.1%
Maintainers (1)
ryan112358
Last synced: 7 months ago

Dependencies

requirements.txt pypi
  • disjoint-set *
  • matplotlib *
  • networkx *
  • nose *
  • numpy *
  • pandas *
  • scipy *
setup.py pypi