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Models/FCN-SNLST

FCN-SNLST

Reported on 16 benchmarks across 1 task · 1 paper · 3 SOTA

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

Time Series16 results

  • Time Series ClassificationonNetFlow
    Accuracy· 2020-06-12
    0.96
    SOTA
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonAUSLAN
    Accuracy· 2020-06-12
    0.993
    SOTA
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonPEMS
    Accuracy· 2020-06-12
    0.857
    SOTA
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonSHAPES
    Accuracy· 2020-06-12
    1
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonLibras
    Accuracy· 2020-06-12
    0.957
    best: 0.97 (MALSTM-FCN)
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonDigitShapes
    Accuracy· 2020-06-12
    1
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonCharacterTrajectories
    Accuracy· 2020-06-12
    0.994
    best: 1 (MALSTM-FCN)
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonPenDigits
    Accuracy· 2020-06-12
    0.953
    best: 0.955 (GP-Sig)
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonArabicDigits
    Accuracy· 2020-06-12
    0.993
    best: 0.9945 (ConvTran)
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonJapaneseVowels
    Accuracy· 2020-06-12
    0.98
    best: 0.99 (MALSTM-FCN)
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonUWave
    Accuracy· 2020-06-12
    0.969
    best: 0.98 (MALSTM-FCN)
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonECG
    Accuracy· 2020-06-12
    0.86
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonWalkvsRun
    Accuracy· 2020-06-12
    1
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonCMUsubject16
    Accuracy· 2020-06-12
    1
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonKickvsPunch
    Accuracy· 2020-06-12
    1
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027
  • Time Series ClassificationonWafer
    Accuracy· 2020-06-12
    0.989
    best: 0.9999513303049968 (R_DST_Ensemble)
    Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor ProjectionsarXiv:2006.07027