Galerkin Neural ODEs

Repository metrics

Stars

919 stars (919 stars)

PR merge metrics

Avg merge 1d 14h (Avg merge 1d 14h)11 merged PRs in 30d (11 merged PRs in 30d)

Description

Contributor guide

Research direction

Study the arXiv paper 2002.08071 on Galerkin Neural ODEs, understand the method, and implement it as a new layer or extension in DiffEqFlux.jl. Use existing neural ODE building blocks and add the Galerkin projection step. Validate with tests.

Tech stack

julia

Domain

machine learningai

Issue type

Feature

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

4

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.

Unclear

Prerequisites

JuliaNeural ODE basicsGit

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

25