TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Multivariate Time Series Forecasting	MuJoCo	RNN GRU-D	MSE (10^-2, 50% missing)	5.833	# 4
Multivariate Time Series Imputation	MuJoCo	RNN GRU-D	MSE (10^2, 50% missing)	0.748	# 4
Time Series Classification	PhysioNet Challenge 2012	GRU-D	AUC	84.24%	# 8
Time Series Classification	PhysioNet Challenge 2012	GRU-D	AUC Stdev	0.012%	# 12

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Recurrent Neural Networks for Multivariate Time Series with Missing Values

6 Jun 2016 • Zhengping Che • Sanjay Purushotham • Kyunghyun Cho • David Sontag • Yan Liu

Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values. In time series prediction and other related tasks, it has been noted that missing values and their missing patterns are often correlated with the target labels, a.k.a., informative missingness... (read more)

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PeterChe1990/GRU-D official

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MULTIVARIATE TIME SERIES FORECASTING

MULTIVARIATE TIME SERIES IMPUTATION

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TIME SERIES ANALYSIS

TIME SERIES CLASSIFICATION

TIME SERIES PREDICTION

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Ranked #4 on Multivariate Time Series Forecasting on MuJoCo

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TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	BENCHMARK
Multivariate Time Series Forecasting	MuJoCo	RNN GRU-D	MSE (10^-2, 50% missing)	5.833	# 4	Compare
Multivariate Time Series Imputation	MuJoCo	RNN GRU-D	MSE (10^2, 50% missing)	0.748	# 4	Compare
Time Series Classification	PhysioNet Challenge 2012	GRU-D	AUC	84.24%	# 8	Compare
Time Series Classification	PhysioNet Challenge 2012	GRU-D	AUC Stdev	0.012%	# 12	Compare

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