Time Series Classification On Pems

Métriques

Accuracy

NLL

Résultats

Résultats de performance de divers modèles sur ce benchmark

			Paper Title
FCN-SNLST	0.857	-	Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
GP-Sig	0.820	0.520	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
GP-KConv1D	0.794	0.537	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
GP-Sig-GRU	0.775	1.100	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
GP-GRU	0.769	0.784	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
GP-Sig-LSTM	0.763	0.704	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
SNLST	0.747	-	Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
GP-LSTM	0.745	1.194	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances

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Time Series Classification On Pems | SOTA | HyperAI