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GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series

NeurIPS 2019 · Time series › Causal and generative time series · approach: Neural differential equations · 167 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
GRU-ODE-Bayes vs best baselinesporadic time series forecasting · MIMIC-IIIMSE: 0.62 -> 0.48Helped
use continuous GRU-ODE cell instead of discretized GRU (ablation)GRU-ODE-Bayes · MIMIC-III 1,000 patientsMSE: 0.87 -> 0.77Helped
use continuous GRU-ODE cell instead of discretized GRU (ablation)GRU-ODE-Bayes · MIMIC-III fullMSE: 0.46 -> 0.48No clear effect
use GRU-Bayes update instead of MLP (ablation)GRU-ODE-Bayes · MIMIC-IIINegLL: 1.05 -> 0.83Helped

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