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ForecastNet: A Time-Variant Deep Feed-Forward Neural Network
  Architecture for Multi-Step-Ahead Time-Series Forecasting
v1v2 (latest)

ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series Forecasting

International Conference on Neural Information Processing (ICONIP), 2020
11 February 2020
J. Dabrowski
Yifan Zhang
Ashfaqur Rahman
    AI4TS
ArXiv (abs)PDFHTML

Papers citing "ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series Forecasting"

7 / 7 papers shown
MatrixNet: Learning over symmetry groups using learned group representations
MatrixNet: Learning over symmetry groups using learned group representationsNeural Information Processing Systems (NeurIPS), 2025
Lucas Laird
Circe Hsu
Asilata Bapat
Robin Walters
AI4CE
243
1
0
17 Jan 2025
Deterministic Guidance Diffusion Model for Probabilistic Weather
  Forecasting
Deterministic Guidance Diffusion Model for Probabilistic Weather Forecasting
Donggeun Yoon
Minseok Seo
Do-Yun Kim
Yeji Choi
Donghyeon Cho
DiffM
374
13
0
05 Dec 2023
Masked Multi-Step Probabilistic Forecasting for Short-to-Mid-Term
  Electricity Demand
Masked Multi-Step Probabilistic Forecasting for Short-to-Mid-Term Electricity DemandIEEE Power & Energy Society General Meeting (PESGM), 2023
Yiwei Fu
Nurali Virani
Honggang Wang
AI4TS
217
8
0
14 Feb 2023
Masked Multi-Step Multivariate Time Series Forecasting with Future
  Information
Masked Multi-Step Multivariate Time Series Forecasting with Future Information
Yiwei Fu
Honggang Wang
Nurali Virani
AI4TS
262
2
0
28 Sep 2022
Deep Learning for Prawn Farming: Forecasting and Anomaly Detection
Deep Learning for Prawn Farming: Forecasting and Anomaly DetectionPacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2022
J. Dabrowski
Ashfaqur Rahman
Andrew D. Hellicar
Mashud Rana
Stuart Arnold
133
3
0
12 May 2022
AutoTS: Automatic Time Series Forecasting Model Design Based on
  Two-Stage Pruning
AutoTS: Automatic Time Series Forecasting Model Design Based on Two-Stage Pruning
Chunnan Wang
Xing-Yu Chen
Chen-Hung Wu
Hongzhi Wang
TPMAI4TS
232
7
0
26 Mar 2022
Achieving an Accurate Random Process Model for PV Power using Cheap
  Data: Leveraging the SDE and Public Weather Reports
Achieving an Accurate Random Process Model for PV Power using Cheap Data: Leveraging the SDE and Public Weather ReportsCSEE Journal of Power and Energy Systems (JPES), 2021
Yiwei Qiu
Jin Lin
Zhipeng Zhou
Ningyi Dai
Feng Liu
Y. Song
166
1
0
27 Nov 2021
1
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