Kernel Based DMD

Repository metrics

Stars

428 stars (428 stars)

PR merge metrics

Avg merge 2d 3h (Avg merge 2d 3h)17 merged PRs in 30d (17 merged PRs in 30d)

Description

Contributor guide

Research direction

Study the Kernel DMD paper (arXiv:1411.2260) and implement the algorithm within the DataDrivenDiffEq.jl framework. Start by understanding the existing DMD implementation and then extend it with kernel methods.

Tech stack

None

Domain

machine learning

Issue type

Feature

DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.

3

Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.

Over 1 week

Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.

Active

ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.

Needs investigation

Prerequisites

Julia

Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.

20