Time Series Classification On Libras

Metrics

Accuracy

NLL

Results

Performance results of various models on this benchmark

			Paper Title
MALSTM-FCN	0.97	-	Multivariate LSTM-FCNs for Time Series Classification
FCN-SNLST	0.957	-	Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
GP-Sig	0.923	0.259	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-GRU	0.899	0.346	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
GP-LSTM	0.776	0.911	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
SNLST	0.773	-	Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
GP-GRU	0.742	1.110	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

0 of 10 row(s) selected.

Time Series Classification On Libras | SOTA | HyperAI