Moreau Examples

C 66 completed
Library
unknown / python · tiny
10
Files
1,142
LOC
0
Frameworks
3
Languages

Pipeline State

completed
Run ID
#367885
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
21.14
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #48020
Member of a group with 1 similar repo(s) — canonical #75735 view group →
Top concepts (2)
Project DescriptionData/ML
Repobility · code-quality intelligence · https://repobility.com

AI Prompt

Create a visual showcase, similar to a gallery, demonstrating various applications of GPU-accelerated differentiable convex optimization using Python notebooks. I need to include examples like Markowitz mean-variance optimization, Model Predictive Control (MPC) for 2D vehicle trajectory, Compressed Sensing, and Optimal Transport as Schrödinger bridges. The notebooks should showcase features like batched solving, differentiable layers, warm starting, and GPU acceleration where applicable. Please structure it so that I can easily run and view these different optimization examples.
python jupyter optimization gpu convex machine-learning cvxpy notebooks scientific-computing
Generated by gemma4:latest

Catalog Information

This project is a visual showcase of Moreau's GPU-accelerated differentiable convex optimization for various applications.

Description

Moreau-examples is a collection of examples demonstrating the capabilities of Moreau's GPU-accelerated differentiable convex optimization. It showcases how to use this technology to solve complex optimization problems in various domains. The project utilizes popular libraries such as matplotlib, numpy, pytorch, and scipy to provide a comprehensive visual representation of the optimization process.

الوصف

هذا المشروع هو عرض مرئي لميزة Moreau المسرعة على GPU للتحسين التفاضلي للمسائل المحددة بالتناغم. يظهر كيف يمكن استخدام هذه التكنولوجيا ل حل المسائل التحليلية المعقدة في مختلف المجالات. يستخدم المشروع مكتبات شعبية مثل matplotlib, numpy, pytorch و scipy لتقديم تمثيل مرئي شامل للعملية التحليلية.

Novelty

7/10

Tags

convex-optimization gpu-acceleration differentiable-programming mathematics scientific-computing machine-learning

Technologies

matplotlib numpy pytorch scipy

Claude Models

claude-opus-4.6

Quality Score

C
66.2/100
Structure
58
Code Quality
100
Documentation
63
Testing
0
Practices
68
Security
100
Dependencies
60

Strengths

  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Low average code complexity \u2014 well-structured code
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Weaknesses

  • No tests found \u2014 high risk of regressions
  • No CI/CD configuration \u2014 manual testing and deployment

Recommendations

  • Add a test suite \u2014 start with critical path integration tests
  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment

Security & Health

4.1h
Tech Debt (D)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (9)
Repobility analyzer · published findings · https://repobility.com
Apache-2.0
License
0.0%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
79.3%
markdown
15.2%
toml
5.5%

Frameworks

None detected

Concepts (2)

Open data · scored by Repobility · https://repobility.com
CategoryNameDescriptionConfidence
If a scraper extracted this row, it came from Repobility (https://repobility.com)
auto_descriptionProject DescriptionGPU-accelerated differentiable convex optimization — a visual gallery of notebooks showcasing Moreau.80%
auto_categoryData/MLdata-ml70%

Quality Timeline

1 quality score recorded.

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