Forecasting Pipeline

Forecasting pipelines automate the process of building predictive models for time series data, aiming to improve accuracy and efficiency across diverse applications. Current research emphasizes the integration of automated machine learning (AutoML) techniques with various model architectures, including statistical methods, machine learning algorithms, and deep neural networks, often within an end-to-end framework. This focus on automation addresses the challenges of handling increasingly complex and diverse datasets, leading to more robust and readily deployable forecasting solutions across fields like weather prediction, energy forecasting, and finance. The resulting improvements in forecasting accuracy and efficiency have significant implications for resource management, risk assessment, and decision-making in numerous sectors.

Papers

October 9, 2024

Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data
Matthew Ashman, Cristiana Diaconu, Eric Langezaal, Adrian Weller, Richard E. Turner
Neural Process Temporal Data Spatiotemporal Datasets Unstructured Information Large Scale Spatio Temporal Transformer Neural Forecasting Pipeline

May 23, 2024

SolNet: Open-source deep learning models for photovoltaic power forecasting across the globe
Joris Depoortere, Johan Driesen, Johan Suykens, Hussain Syed Kazmi
Deep Learning Model Open Source Day Ahead Globe Ce Forecasting Pipeline

March 30, 2024

Aardvark weather: end-to-end data-driven weather forecasting
Anna Vaughan, Stratis Markou, Will Tebbutt, James Requeima, Wessel P. Bruinsma, Tom R. Andersson, Michael Herzog, Nicholas D. Lane, Matthew Chantry, J. Scott Hosking, Richard E. Turner
Data Driven Medium Range Data Driven Weather Forecasting Pipeline

December 13, 2023

auto-sktime: Automated Time Series Forecasting
Marc-André Zöller, Marius Lindauer, Marco F. Huber
Time Series Forecasting Real World Time Series Efficient Time Series Forecasting Forecasting Pipeline

April 8, 2023

OFTER: An Online Pipeline for Time Series Forecasting
Nikolas Michael, Mihai Cucuringu, Sam Howison
Time Series Forecasting Forecasting Pipeline

February 3, 2022

Review of automated time series forecasting pipelines
Stefan Meisenbacher, Marian Turowski, Kaleb Phipps, Martin Rätz, Dirk Müller, Veit Hagenmeyer, Ralf Mikut
Time Series Narrative Review Time Series Forecasting Forecasting Model Forecasting Method Energy Pipeline Forecasting Pipeline

December 22, 2021

Dynamic Combination of Heterogeneous Models for Hierarchical Time Series
Xing Han, Jing Hu, Joydeep Ghosh
Forecasting Model Heterogeneous Model Item Combination Hierarchical Time Series Quantile Forecast Forecasting Pipeline