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• W3181461345 abstract "Here, we propose a general method for probabilistic time series forecasting. We combine an autoregressive recurrent neural network to model temporal dynamics with Implicit Quantile Networks to learn a large class of distributions over a time-series target. When compared to other probabilistic neural forecasting models on real- and simulated data, our approach is favorable in terms of point-wise prediction accuracy as well as on estimating the underlying temporal distribution." @default.
• W3181461345 created "2021-07-19" @default.
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• W3181461345 date "2021-07-08" @default.
• W3181461345 modified "2023-09-27" @default.
• W3181461345 title "Probabilistic Time Series Forecasting with Implicit Quantile Networks." @default.
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