Accueil Actualités Articles de recherche récents Tutoriels Ensembles de données Wiki SOTA Modèles LLM Classement GPU Événements

Français

Time Series Classification On Japanesevowels

Métriques

Accuracy

NLL

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy	NLL	Paper Title	Repository
GP-Sig-LSTM	0.981	0.080	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
GP-Sig	0.982	0.069	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
GP-KConv1D	0.986	0.067	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
GP-LSTM	0.982	0.061	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
GP-Sig-GRU	0.985	0.053	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
GP-GRU	0.986	0.052	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances	-
MALSTM-FCN	0.99	-	Multivariate LSTM-FCNs for Time Series Classification	-
SNLST	0.979	-	Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections	-
FCN-SNLST	0.980	-	Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections	-
ConvTran	0.9891	-	Improving Position Encoding of Transformers for Multivariate Time Series Classification	-

0 of 10 row(s) selected.

Time Series Classification On Japanesevowels | SOTA | HyperAI