lanl/Yoke
Jul 2025 – Aug 2025
2 Months active
Languages Used
PythonCSV
Technical Skills
Data AugmentationDeep LearningModel TrainingCode RefactoringData FormattingData Management
ryanw18
PROFILE
Ryanw18
Ryan Wang developed and enhanced data augmentation and formatting features for the lanl/Yoke repository over a two-month period. He implemented Gaussian noise injection for LodeRunner model training, introducing a noise_scale parameter that applies noise proportional to the input’s L2 norm, thereby improving training robustness and reproducibility. Using Python and CSV, Ryan also refined string formatting logic to increase numeric precision in configuration files, supporting more accurate experiment tracking. His work included code refactoring and data management, such as cleaning up legacy code and adding new datasets, which improved code maintainability and facilitated more reliable deep learning experimentation workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
3
Lines of code
40
Activity Months2
Your Network
24 peopleSame Organization
@colostate.edu10
Shared Repositories
14
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Work History
August 2025
3 Commits • 2 Features
Aug 1, 2025Concise monthly summary for 2025-08 (lanl/Yoke): highlights key feature deliveries, code quality improvements, and the resulting business impact.
3 Commits • 2 Features
Aug 1, 2025Concise monthly summary for 2025-08 (lanl/Yoke): highlights key feature deliveries, code quality improvements, and the resulting business impact.
August 2025
July 2025
1 Commits • 1 Features
Jul 1, 2025Month: 2025-07 — Lanl/Yoke: Implemented Gaussian Noise injection via a noise_scale parameter for LodeRunner training. The noise is scaled by the input's L2 norm and integrated into training input templates and the model forward pass to enable controlled data augmentation and improved robustness. This work enhances training stability and generalization while enabling reproducible experiments. Commit tracked: 147b8b502ed4ad21b0c41821c16439beec6de85d ("adding noise functionality").
July 2025
1 Commits • 1 Features
Jul 1, 2025Month: 2025-07 — Lanl/Yoke: Implemented Gaussian Noise injection via a noise_scale parameter for LodeRunner training. The noise is scaled by the input's L2 norm and integrated into training input templates and the model forward pass to enable controlled data augmentation and improved robustness. This work enhances training stability and generalization while enabling reproducible experiments. Commit tracked: 147b8b502ed4ad21b0c41821c16439beec6de85d ("adding noise functionality").
Activity
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Quality Metrics
Correctness85.0%
Maintainability85.0%
Architecture75.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVPython
Technical Skills
Code RefactoringData AugmentationData FormattingData ManagementData RepresentationDeep LearningModel TrainingString FormattingString Manipulation
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline