RRepoGEO

REPOGEO REPORT · LITE

openai/InfoGAN

Default branch master · commit 6e412323 · scanned 5/24/2026, 11:03:11 AM

GitHub: 1,069 stars · 301 forks

AI VISIBILITY SCORE
79 /100
Needs work
Category recall
2 / 2
Avg rank #3.5 when recommended
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 openai/InfoGAN, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with the text of a standard open-source license (e.g., MIT or Apache-2.0).
  • hightopics#2
    Expand repository topics for better categorization

    Why:

    CURRENT
    paper
    COPY-PASTE FIX
    generative-adversarial-networks, gan, disentangled-representations, unsupervised-learning, deep-learning, machine-learning, tensorflow, research-code
  • mediumreadme#3
    Reposition README H1 to emphasize GANs for disentanglement

    Why:

    CURRENT
    # InfoGAN
    COPY-PASTE FIX
    # InfoGAN: Generative Adversarial Networks for Disentangled Representations

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
2 / 2
100% of queries surface openai/InfoGAN
Avg rank
#3.5
Lower is better. #1 = top recommendation.
Share of voice
10%
Of all named tools, what % are you?
Top rival
deepmind/disentanglement_lib
Recommended in 3 of 2 queries
COMPETITOR LEADERBOARD
  1. deepmind/disentanglement_lib · recommended 3×
  2. StyleGAN · recommended 2×
  3. Variational Autoencoders (VAEs) · recommended 1×
  4. disentangled VAE · recommended 1×
  5. Adversarial Autoencoders (AAEs) · recommended 1×
  • CATEGORY QUERY
    How can I learn disentangled and interpretable representations from unlabeled image data?
    you: #6
    AI recommended (in order):
    1. Variational Autoencoders (VAEs)
    2. β-VAE (deepmind/disentanglement_lib)
    3. FactorVAE (deepmind/disentanglement_lib)
    4. disentangled VAE
    5. Adversarial Autoencoders (AAEs)
    6. InfoGAN ← you
    7. SimCLR
    8. BYOL
    9. DINO
    10. GANSformer
    11. StyleGAN
    12. StyleGAN2
    13. StyleGAN3
    14. DIP-VAE (deepmind/disentanglement_lib)
    Show full AI answer
  • CATEGORY QUERY
    What generative adversarial network approaches enable discovering latent factors in data?
    you: #1
    AI recommended (in order):
    1. InfoGAN ← you
    2. FactorGAN
    3. β-VAE-GAN
    4. StyleGAN
    5. Adversarial Latent Autoencoders (ALAE)
    6. Conditional GANs (cGANs)
    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 openai/InfoGAN?
    pass
    AI named openai/InfoGAN explicitly

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

  • If a team adopts openai/InfoGAN in production, what risks or prerequisites should they evaluate first?
    pass
    AI named openai/InfoGAN 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 openai/InfoGAN solve, and who is the primary audience?
    pass
    AI named openai/InfoGAN explicitly

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

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openai/InfoGAN — 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