Time Series Classification On Cmusubject16

Metriken

Accuracy

NLL

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

			Paper Title
GP-Sig-LSTM	1.000	0.088	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
MALSTM-FCN	1	-	Multivariate LSTM-FCNs for Time Series Classification
FCN-SNLST	1	-	Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
GP-Sig-GRU	1.000	0.040	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
SNLST	1	-	Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections
GP-GRU	0.993	0.089	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
GP-Sig	0.979	0.089	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
GP-LSTM	0.924	0.270	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
GP-KConv1D	0.897	0.255	Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances

0 of 9 row(s) selected.

Time Series Classification On Cmusubject16 | SOTA | HyperAI