MeasureTransport / MeasureTransport/MParT

MapFromSamples

Open
#336 2 comments 0 reactions 0 assignees View on GitHub

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enhancement
Dominant language
C++
Stars
18
Forks
5
PR merge metrics
No merged PRs in 30d

Description

An easy wrapper that performs the following steps

  1. Standardize the samples
  2. Reorder the dimensions to maximize conditional independence *
  3. Estimate conditional independence structure in the map *
    4a) Train a map according to a specific total order OR
    4b) Adaptively learn a map using ATM or something
  4. compose the standardization, reordering, and learnt map somehow
  5. return that composition
    The steps with * are optional. Related to #334 #317 #312

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No source file or test is named. Start by reading related issues #334, #317, and #312 and locating the existing map, standardization, and sample-handling entry points. Done would require an agreed wrapper that performs the listed pipeline, supports the optional steps, and returns the composed map.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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