# Zymrael/awesome-neural-ode

A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.

Repository: https://github.com/Zymrael/awesome-neural-ode
Canonical: https://ross.abutalabs.com/products/awesome-neural-ode
License: MIT
License Family: permissive
Topics: deep-learning, ordinary-differential-equations, dynamical-systems, dynamical-modeling, ode-solver, ode, hamiltonian-dynamics, implicit-models, root-finding
Last push: 2024-09-13T16:20:13+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2607, "days_push": 719, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1544, forks 154 (observed 2026-08-28T04:05:01.459177+00:00)

## What it is
A curated awesome-list of research papers, code, and resources on Neural ODEs and the interplay between differential equations, deep learning, dynamical systems, control, and numerical methods. It categorizes works by topic such as Neural ODEs, SDEs, CDEs, generative models, and scientific machine learning.

## Use cases
- find papers on neural ordinary differential equations
- learn about continuous-depth deep learning models
- discover libraries for solving ODEs with neural networks
- research dynamical systems approaches to deep learning
- find resources on neural operators and PDE solvers
- explore scientific machine learning literature
- find code implementations of neural ODE architectures

## When to choose
- you need a curated starting point for neural ODE research
- you want links to papers and code on differential equations in deep learning
- you are exploring scientific machine learning topics

## When to avoid
- you need a runnable software library rather than a resource list
- you need production tooling for ODE solving
- you want tutorials with hands-on exercises rather than paper links

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, simulation, math
- domain: machine-learning, deep-learning, tutorials, awesome-lists
- platform: cross-platform
- tags: neural-ode, differential-equations, dynamical-systems, scientific-machine-learning, awesome-list, papers, ode-solver, control-theory, algorithms

## Member repositories
- Zymrael/awesome-neural-ode (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:01.459177+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:30:37.211398+00:00, confidence not recorded.
  - readme: https://github.com/Zymrael/awesome-neural-ode (fetched 2026-08-28T04:05:01.459177+00:00, sha f71b9920c934)
- Data as of 2026-08-30T08:39:29.467469+00:00.