Reference change · event page
Reference changes · DOI
International Journal of Forecasting 36, 1181–1191
Published notice on a work cited in the Pith corpus. Exact quotes below. No model judges whether any citation was load-bearing.
This page records that a citing paper's bibliography includes a work with a published notice. It is not a judgment on the citing paper.
Correction
Crossref
6 open · 6 total · 0 disputed
- Event date
- 2021-05-19
01One-hop citing occurrences
Correction
Open
Autoregressive Learning in Joint KL: Sharp Oracle Bounds and Lower Bounds
ref [60] ·
2605.12316
· notice #6673
· dispute
Raw extraction · bibliography line
David Salinas and Valentin Flunkert and Jan Gasthaus and Tim Januschowski , keywords =. DeepAR: Probabilistic forecasting with autoregressive recurrent networks , journal =. 2020 , issn =. doi:https://doi.org/10.1016/j.ijforecast.2019.07.001 , url =
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David Salinas and Valentin Flunkert and Jan Gasthaus and Tim Januschowski, keywords =. DeepAR: Probabilistic forecasting with autoregressive recurrent networks, journal =. 2020, issn =. doi:https://doi.org/10.1016/j.ijforecast.2019.07.001, url =
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CAST: Causal Anchored Simplex Transport for Distribution-Valued Time Series
ref [20] ·
2605.16919
· notice #6674
· dispute
Raw extraction · bibliography line
David Salinas, Valentin Flunkert, Jan Gasthaus, and Tim Januschowski. DeepAR: Probabilistic forecasting with autoregressive recurrent networks.International Journal of Forecasting, 36(3):1181–1191, 2020. doi: 10.1016/j.ijforecast.2019.07.001. 10
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Stabilizing distribution-free probabilistic forecasts
ref [38] ·
2605.28531
· notice #6678
· dispute
Raw extraction · bibliography line
DeepAR:Probabilisticforecastingwithautoregressive recurrent networks. International Journal of Forecasting 36, 1181–1191. doi:10.1016/j.ijforecast.2019.07.001. Spiliotis, E., Petropoulos, F.,
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DeepAR:Probabilisticforecastingwithautoregressive recurrent networks. International Journal of Forecasting 36, 1181–1191. doi:10.1016/j.ijforecast.2019.07.001. Spiliotis, E., Petropoulos, F
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Open
Dirichlet-Guided Group Forecasting for Alleviating Over-smoothing in Time Series Forecasting
ref [149] ·
2606.10592
· notice #6677
· dispute
Raw extraction · bibliography line
David Salinas and Valentin Flunkert and Jan Gasthaus and Tim Januschowski , keywords =. DeepAR: Probabilistic forecasting with autoregressive recurrent networks , journal =. 2020 , issn =. doi:https://doi.org/10.1016/j.ijforecast.2019.07.001 , url =
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David Salinas and Valentin Flunkert and Jan Gasthaus and Tim Januschowski, keywords =. DeepAR: Probabilistic forecasting with autoregressive recurrent networks, journal =. 2020, issn =. doi:https://doi.org/10.1016/j.ijforecast.2019.07.001, url =
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CloudCons: A Comprehensive End-to-End Benchmark for Cloud Resource Consolidation
ref [16] ·
2606.13513
· notice #6676
· dispute
Raw extraction · bibliography line
Valentin Flunkert, David Salinas, and Jan Gasthaus. 2017. DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks.International Journal of Forecasting36 (04 2017). doi:10.1016/j.ijforecast.2019.07.001
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ConTex: Reformulating Counterfactual Generation For Time Series Forecasting
ref [19] ·
2606.18049
· notice #6675
· dispute
Raw extraction · bibliography line
ISSN 0169-2070. doi: https://doi.org/10.1016/j.ijforecast.2019.07.001. URL https://www.sciencedirect.com/science/article/pii/S0169207019301888. Udo Schlegel and Thomas Seidl. What-if explanations over time: Counterfactuals for time series classification,
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ISSN 0169-2070. doi: https://doi.org/10.1016/j.ijforecast.2019.07.001. URL https://www.sciencedirect.com/science/article/pii/S0169207019301888. Udo Schlegel and Thomas Seidl. What-if explanations over time: Counterfactuals for time series classification