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added additional loss against data for NNODE #666

Merged
merged 53 commits into from
Apr 4, 2023
Merged

added additional loss against data for NNODE #666

merged 53 commits into from
Apr 4, 2023

Commits on Apr 4, 2023

  1. added additional loss against data for NNODE(still needs reviewing)

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  2. Added additional Loss function Feature for NNODE 

    (user defined function), also now has common OptimizationFunction object
definition(instead for each TrainingStrategy).
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  3. Added Tests for additional_loss function feature 

    Also updated docs(might need further editing)
Future Scope:
We can add weighted loss in NNODE,and even losses for
Parameter Estimation for Inverse Problems.
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  4. formatted files

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  5. docs

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  6. Docs for new NNODE Argument:additional_loss

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  7. fixed optimizations choice

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  8. rebased

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  9. added additional loss against data for NNODE(still needs reviewing)

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  10. Added additional Loss function Feature for NNODE 

    (user defined function), also now has common OptimizationFunction object
definition(instead for each TrainingStrategy).
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  11. Added Tests for additional_loss function feature 

    Also updated docs(might need further editing)
Future Scope:
We can add weighted loss in NNODE,and even losses for
Parameter Estimation for Inverse Problems.
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  12. docs

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  13. Mixed my PR with PR SciML#635 by sdesai1287

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  14. fixed optimizations choice

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  15. added additional loss against data for NNODE(still needs reviewing)

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  16. Added additional Loss function Feature for NNODE 

    (user defined function), also now has common OptimizationFunction object
definition(instead for each TrainingStrategy).
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  17. Added Tests for additional_loss function feature 

    Also updated docs(might need further editing)
Future Scope:
We can add weighted loss in NNODE,and even losses for
Parameter Estimation for Inverse Problems.
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  18. docs

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  19. Mixed my PR with PR SciML#635 by sdesai1287

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  20. fixed optimizations choice

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  21. added additional loss against data for NNODE(still needs reviewing)

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  22. Added additional Loss function Feature for NNODE 

    (user defined function), also now has common OptimizationFunction object
definition(instead for each TrainingStrategy).
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  23. Added Tests for additional_loss function feature 

    Also updated docs(might need further editing)
Future Scope:
We can add weighted loss in NNODE,and even losses for
Parameter Estimation for Inverse Problems.
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  24. formatted files

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  25. docs

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  26. Mixed my PR with PR SciML#635 by sdesai1287

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  27. fixed optimizations choice

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  28. rebased

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  29. Actually performed Rebase and Formatted some files

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  30. fixed ode_solve.jl rebase issues

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  31. added additional loss against data for NNODE(still needs reviewing)

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  32. Added additional Loss function Feature for NNODE 

    (user defined function), also now has common OptimizationFunction object
definition(instead for each TrainingStrategy).
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  33. Added Tests for additional_loss function feature 

    Also updated docs(might need further editing)
Future Scope:
We can add weighted loss in NNODE,and even losses for
Parameter Estimation for Inverse Problems.
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  34. formatted files

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  35. docs

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  36. Mixed my PR with PR SciML#635 by sdesai1287

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  37. fixed optimizations choice

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  38. rebased

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  39. Actually performed Rebase and Formatted some files

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  40. fixed ode_solve.jl rebase issues

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  41. .

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  42. added additional loss against data for NNODE(still needs reviewing)

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  43. Added additional Loss function Feature for NNODE 

    (user defined function), also now has common OptimizationFunction object
definition(instead for each TrainingStrategy).
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  44. Added Tests for additional_loss function feature 

    Also updated docs(might need further editing)
Future Scope:
We can add weighted loss in NNODE,and even losses for
Parameter Estimation for Inverse Problems.
    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  45. docs

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  46. Mixed my PR with PR SciML#635 by sdesai1287

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  47. fixed optimizations choice

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  48. Actually performed Rebase and Formatted some files

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  49. rebase Fr Fr

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  50. stuff happened

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  51. Fixed Tests line 208 NNODE_tests

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  52. changes from review

    @AstitvaAggarwal
    AstitvaAggarwal committed Apr 4, 2023
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  53. Update src/ode_solve.jl

    @ChrisRackauckas
    ChrisRackauckas authored Apr 4, 2023
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