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Models/Neural Network

Neural Network

Reported on 8 benchmarks across 1 task · 1 paper · 8 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology8 results

  • regressiononConcrete Compressive Strength
    R2 Score· 2025-06-13
    0.8588
    SOTA
    Fidelity Isn't Accuracy: When Linearly Decodable Functions Fail to Match the Ground TrutharXiv:2506.12176
  • regressiononConcrete Compressive Strength
    lambda· 2025-06-13
    0.6659
    SOTA
    Fidelity Isn't Accuracy: When Linearly Decodable Functions Fail to Match the Ground TrutharXiv:2506.12176
  • regressiononMedical Cost Personal Dataset
    R2 Score· 2025-06-13
    0.8673
    SOTA
    Fidelity Isn't Accuracy: When Linearly Decodable Functions Fail to Match the Ground TrutharXiv:2506.12176
  • regressiononMedical Cost Personal Dataset
    lambda· 2025-06-13
    0.9186
    SOTA
    Fidelity Isn't Accuracy: When Linearly Decodable Functions Fail to Match the Ground TrutharXiv:2506.12176
  • regressiononSynthetic: y = x * sin x
    R2 Score· 2025-06-13
    0.9755
    SOTA
    Fidelity Isn't Accuracy: When Linearly Decodable Functions Fail to Match the Ground TrutharXiv:2506.12176
  • regressiononSynthetic: y = x * sin x
    lambda· 2025-06-13
    -0.0105
    SOTA
    Fidelity Isn't Accuracy: When Linearly Decodable Functions Fail to Match the Ground TrutharXiv:2506.12176
  • regressiononCalifornia Housing Prices
    R2 Score· 2025-06-13
    0.7908
    SOTA
    Fidelity Isn't Accuracy: When Linearly Decodable Functions Fail to Match the Ground TrutharXiv:2506.12176
  • regressiononCalifornia Housing Prices
    lambda· 2025-06-13
    0.6968
    SOTA
    Fidelity Isn't Accuracy: When Linearly Decodable Functions Fail to Match the Ground TrutharXiv:2506.12176