RRepoGEO

REPOGEO REPORT · LITE

Zymrael/awesome-neural-ode

Default branch master · commit 37f00d2a · scanned 6/24/2026, 8:47:44 PM

GitHub: 1,533 stars · 155 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface Zymrael/awesome-neural-ode, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening sentence to explicitly state it's an 'awesome list'

    Why:

    CURRENT
    A collection of resources regarding the interplay between differential equations, dynamical systems, deep learning, control, numerical methods and scientific machine learning.
    COPY-PASTE FIX
    This is an awesome list: a curated collection of resources regarding the interplay between differential equations, dynamical systems, deep learning, control, numerical methods and scientific machine learning.
  • hightopics#2
    Add 'awesome-list' to the repository topics

    Why:

    CURRENT
    deep-learning, dynamical-modeling, dynamical-systems, hamiltonian-dynamics, implicit-models, ode, ode-solver, ordinary-differential-equations, root-finding
    COPY-PASTE FIX
    awesome-list, deep-learning, dynamical-modeling, dynamical-systems, hamiltonian-dynamics, implicit-models, ode, ode-solver, ordinary-differential-equations, root-finding
  • mediumhomepage#3
    Add the repository URL as the homepage in the About section

    Why:

    COPY-PASTE FIX
    https://github.com/Zymrael/awesome-neural-ode

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface Zymrael/awesome-neural-ode
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DeepXDE
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. DeepXDE · recommended 1×
  2. SciML (Julia) · recommended 1×
  3. DiffEqFlux.jl · recommended 1×
  4. NeuralPDE.jl · recommended 1×
  5. TensorFlow Physics (tf_physics) · recommended 1×
  • CATEGORY QUERY
    How can I use deep learning models to solve complex ordinary differential equations?
    you: not recommended
    AI recommended (in order):
    1. DeepXDE
    2. SciML (Julia)
    3. DiffEqFlux.jl
    4. NeuralPDE.jl
    5. TensorFlow Physics (tf_physics)
    6. PyTorch
    7. JAX
    8. haiku
    9. flax
    10. Modulus (NVIDIA)

    AI recommended 10 alternatives but never named Zymrael/awesome-neural-ode. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking resources on applying continuous deep learning models for dynamic system control problems.
    you: not recommended
    AI recommended (in order):
    1. Stable Baselines3 (DLR-RM/stable-baselines3)
    2. Ray RLlib (ray-project/ray)
    3. OpenAI Gym/Farama Gymnasium (Farama-Foundation/Gymnasium)
    4. TensorFlow (tensorflow/tensorflow)
    5. PyTorch (pytorch/pytorch)
    6. JAX (google/jax)
    7. CasADi (casadi/casadi)
    8. ACADO Toolkit (acado/acado)
    9. CVXPY (cvxgrp/cvxpy)
    10. torchdiffeq (rtqichen/torchdiffeq)
    11. DiffEqFlux.jl (SciML/DiffEqFlux.jl)
    12. MATLAB System Identification Toolbox
    13. Python Control Systems Library (python-control/python-control)
    14. MuJoCo (deepmind/mujoco)
    15. PyBullet (bulletphysics/bullet3)
    16. Gazebo (osrf/gazebo)
    17. Unity ML-Agents (Unity-Technologies/ml-agents)

    AI recommended 17 alternatives but never named Zymrael/awesome-neural-ode. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of Zymrael/awesome-neural-ode?
    pass
    AI did not name Zymrael/awesome-neural-ode — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts Zymrael/awesome-neural-ode in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Zymrael/awesome-neural-ode explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo Zymrael/awesome-neural-ode solve, and who is the primary audience?
    pass
    AI did not name Zymrael/awesome-neural-ode — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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Zymrael/awesome-neural-ode — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite