necatiincekara/architecture
.claude/skills/architecture/SKILL.md
Model mimarisi tasarla veya analiz et. Mevcut OCR-QML calismasinda trainable, non-trainable ve classical baseline yollarini guncel duruma gore ele al.
development
Updated Apr 16, 2026
$ install --global
skillsauthnpx skillsauth add necatiincekara/Quanvolutional-Neural-Network architectureInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- architecture
- description:
- Model mimarisi tasarla veya analiz et. Mevcut OCR-QML calismasinda trainable, non-trainable ve classical baseline yollarini guncel duruma gore ele al.
- disable-model-invocation:
- true
Model Architecture Design
Bu skill tarihsel V7-V10 hedeflerini oldugu gibi tekrar etmek icin degil, mevcut repo gercegine gore mimari karar vermek icin kullanilir.
Adimlar
- Once su dosyalari incele:
src/model.pysrc/trainable_quantum_model.pysrc/ablation_models.pysrc/thesis_models.pysrc/benchmark_protocol.pytrain_ablation_local.pytrain_thesis_models.pydocs/PUBLICATION_STRATEGY_2026-03-22.md
- Islem turunu belirle:
analyze: mevcut mimariyi acikla, bottleneck ve parametre dagilimini verhqnn2: tezdeki HQNN-II faithful reproduction planlabaseline: guclu classical baseline ekletrainable: trainable quantum yolunda iyilestirme planla
- Tasarimda su sorulara cevap ver:
- Bu degisiklik adil karsilastirma mi sagliyor?
- Parametre ve veri butcesi makul mu?
- Yayin stratejisine hizmet ediyor mu?
- Cikti olarak sun:
- kisa mimari diagrami
- beklenen avantaj / risk
- parametre etkisi
- egitim maliyeti tahmini
Notlar
- "Quantum advantage" varsayma.
- Mimari oneriyi current-best classical baseline'lara gore degerlendir.
- Tezle devam edilecekse HQNN-II ile bugunku Henderson-style non-trainable modeli karistirma.
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