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Time Series Classification On Wafer

Metrics

Accuracy
NLL

Results

Performance results of various models on this benchmark

Model Name
Accuracy
NLL
Paper TitleRepository
GP-LSTM0.9660.105Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances-
MALSTM-FCN0.99-Multivariate LSTM-FCNs for Time Series Classification-
SNLST0.981-Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections-
GP-GRU0.9940.029Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances-
GP-Sig-GRU0.9780.081Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances-
GP-Sig0.9650.105Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances-
GP-KConv1D0.9840.085Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances-
FCN-SNLST0.989-Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections-
GP-Sig-LSTM0.9880.048Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances-
R_DST_Ensemble0.9999513303049968-Random Dilated Shapelet Transform: A New Approach for Time Series Shapelets-
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Time Series Classification On Wafer | SOTA | HyperAI