QMCSoftware/QMCSoftware
Jun 2025 – Jun 2025
1 Month active
Languages Used
C++CUDAPyTorchPython
Technical Skills
Code ManagementCode RefactoringDeep LearningDependency ManagementDocumentationEnvironment Management
Ally Pascual Kwan
PROFILE
Ally Pascual Kwan
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
11Total
Bugs
0
Commits
11
Features
1
Lines of code
1,357
Activity Months1
Your Network
14 people
Work History
June 2025
11 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for QMCSoftware/QMCSoftware focusing on feature delivery, bug fixes, and business impact. Delivered the MPMC: Neural Network-based Low-Discrepancy Point Sets, introducing an MPMC class for generating low-discrepancy point sets via a Message Passing Neural Network (MPNN) with PyTorch integration. This work includes discrepancy functions, an interactive parameter setup, sample generation, and a robust environment/user-experience flow. Also refactored discrepancy calculations, parameter handling, and maintained MPMC draft files; added documentation to the MPMC class; and implemented robustness improvements around version/package error handling. Cleaned up draft/codebase by removing obsolete mpmc_draft.py to reduce maintenance overhead and potential confusion.
11 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for QMCSoftware/QMCSoftware focusing on feature delivery, bug fixes, and business impact. Delivered the MPMC: Neural Network-based Low-Discrepancy Point Sets, introducing an MPMC class for generating low-discrepancy point sets via a Message Passing Neural Network (MPNN) with PyTorch integration. This work includes discrepancy functions, an interactive parameter setup, sample generation, and a robust environment/user-experience flow. Also refactored discrepancy calculations, parameter handling, and maintained MPMC draft files; added documentation to the MPMC class; and implemented robustness improvements around version/package error handling. Cleaned up draft/codebase by removing obsolete mpmc_draft.py to reduce maintenance overhead and potential confusion.
June 2025
Activity
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Quality Metrics
Correctness78.2%
Maintainability77.2%
Architecture71.8%
Performance67.2%
AI Usage21.8%
Skills & Technologies
Programming Languages
C++CUDAPyTorchPython
Technical Skills
Code ManagementCode RefactoringDeep LearningDependency ManagementDocumentationEnvironment ManagementError HandlingMachine LearningNeural NetworksNumerical MethodsPyTorchPython ScriptingQuasi-Monte Carlo MethodsScientific ComputingScripting
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