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| id | title | status | priority | created | last_updated | owner | github_issue | dependencies | tags | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| parameter-tying-framework | Design parameter tying framework for GPy multioutput kernels | Ready | High | 2025-08-15 | 2025-08-15 | Neil Lawrence |
|
Investigate parameter tying limitations and create CIP for discussion
Description
During LFM kernel code review, we identified that GPy lacks systematic parameter tying capabilities compared to GPmat's modelTieParam() functionality. This limitation affects combination kernels such as multiouptut or additive kernels. We need to investigate the scope of this problem and create a CIP to discuss potential solutions with the community.
Problem Statement
- Current Limitation: GPy's parameter system doesn't support tying parameters across different kernel components
- Impact on LFM: Forces complex parameter handling in EQ_ODE1 and EQ_ODE2 kernels
- Broader Impact: May affect other multiple kernel scenarios where parameters should be shared
- Comparison: GPmat has
modelTieParam()functionality that GPy lacks
Investigation Needed
1. Scope Assessment
- Search existing GitHub issues for parameter tying discussions
- Identify other kernels/models that could benefit from parameter tying
- Assess impact on current GPy codebase
2. Community Input
- Create GitHub issue and associated CIP to discuss parameter tying needs
- Gather feedback from GPy maintainers and users
- Identify use cases beyond LFM kernels
- Assess priority relative to other GPy improvements
3. Technical Analysis
- Analyze GPmat's parameter tying implementation
- Review GPy's current parameter system architecture
- Identify potential integration points
- Assess complexity and maintenance burden
Acceptance Criteria
- Complete investigation of existing GitHub issues and discussions
- Document scope of parameter tying needs across GPy
- Create CIP for parameter tying framework discussion
- Gather community feedback on approach and priority
- Provide recommendations for next steps
Implementation Notes
- Focus on problem identification and community discussion
- Avoid prescribing specific solutions until community input is gathered
- Consider whether this should be a separate CIP or part of broader multioutput improvements
- Document trade-offs between different approaches
Related
- CIP: 0001 (LFM kernel implementation) - may depend on parameter tying
- GPy parameter system design
- GPmat parameter tying implementation
- Multioutput kernel architecture discussions
Progress Updates
2025-08-15
Task created after identifying parameter tying as a potential limitation during LFM kernel code review. Need to investigate scope and create CIP for community discussion.