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- Add code review task for existing LFM implementations - Add design task for modern LFM kernel architecture - Add implementation task for core LFM kernel functionality - Establish clear task dependencies and acceptance criteria - Link to CIP-0001 and relevant papers
58 lines
2.1 KiB
Markdown
58 lines
2.1 KiB
Markdown
---
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id: "design-modern-lfm-kernel"
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title: "Design modern LFM kernel architecture"
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status: "Proposed"
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priority: "High"
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created: "2025-08-15"
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last_updated: "2025-08-15"
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owner: "Neil Lawrence"
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dependencies: ["lfm-kernel-code-review"]
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tags:
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- lfm
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- kernel
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- design
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- architecture
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---
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# Design modern LFM kernel architecture
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## Description
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Design a modern LFM kernel implementation that follows GPy's current architectural patterns and uses the multioutput kernel approach with output index as input.
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## Background
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- Current GPy LFM implementations don't use the modern multioutput kernel approach
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- Need to design a unified LFM kernel that integrates well with GPy's current framework
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- Should maintain backward compatibility while providing improved functionality
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## Design Requirements
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- [ ] Use GPy's multioutput kernel approach with output index as input
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- [ ] Follow consistent API design with other GPy kernels
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- [ ] Implement proper parameter handling and constraints
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- [ ] Support different base kernels for latent functions
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- [ ] Enable efficient gradient computation
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- [ ] Maintain backward compatibility with existing implementations
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## Design Tasks
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- [ ] Define kernel class structure and inheritance hierarchy
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- [ ] Design parameter handling for mass, damper, spring, sensitivity, delay
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- [ ] Plan integration with GPy's multioutput framework
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- [ ] Design cross-kernel computation methods
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- [ ] Plan parameter tying and constraint handling
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- [ ] Design efficient computation methods for large datasets
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## Acceptance Criteria
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- [ ] Complete design specification document
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- [ ] API design that follows GPy patterns
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- [ ] Integration plan with existing GPy infrastructure
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- [ ] Performance considerations documented
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- [ ] Backward compatibility strategy defined
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## Implementation Notes
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- Study how other multioutput kernels in GPy handle output indices
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- Consider parameter tying approaches from MATLAB implementation
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- Design for extensibility to different differential equation types
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- Plan for efficient computation of cross-kernel terms
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## Related
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- CIP: 0001 (LFM kernel implementation)
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- Backlog: lfm-kernel-code-review
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