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Time Series Classification On Libras

Metrics

Accuracy

NLL

Results

Performance results of various models on this benchmark

Model Name	Accuracy	NLL	Paper Title	Repository
GP-GRU	0.742	1.110	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
GP-Sig-LSTM	0.921	0.320	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
GP-Sig	0.923	0.259	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
GP-KConv1D	0.698	1.608	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
TSEM	0.372	-	TSEM: Temporally Weighted Spatiotemporal Explainable Neural Network for Multivariate Time Series	-
SNLST	0.773	-	Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections	-
FCN-SNLST	0.957	-	Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections	-
GP-LSTM	0.776	0.911	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
MALSTM-FCN	0.97	-	Multivariate LSTM-FCNs for Time Series Classification	-
GP-Sig-GRU	0.899	0.346	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-

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Time Series Classification On Libras | SOTA | HyperAI