Forecast Evaluation for Data Scientists: Common Pitfalls and Best Practices

21 March 2022

Papers citing "Forecast Evaluation for Data Scientists: Common Pitfalls and Best Practices"

21 / 21 papers shown

Title
Do global forecasting models require frequent retraining? Marco Zanotti 30 0 0 01 May 2025
ModelRadar: Aspect-based Forecast Evaluation Vítor Cerqueira Luis Roque Carlos Soares 45 0 0 31 Mar 2025
Adaptive parameters identification for nonlinear dynamics using deep permutation invariant networks Mouad Elaarabi Domenico Borzacchiello Yves Le Guennec Philippe Le Bot Sebastien Comas-Cardona 66 0 0 20 Jan 2025
Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting Zongjiang Shang Ling Chen Binqing Wu Dongliang Cui AI4TS AI4CE 26 1 0 31 Oct 2024
An Evaluation of Standard Statistical Models and LLMs on Time Series Forecasting Rui Cao Qiao Wang 27 1 0 09 Aug 2024
Scalable Transformer for High Dimensional Multivariate Time Series Forecasting Xin Zhou Weiqing Wang Wray L. Buntine Shilin Qu Abishek Sriramulu Weicong Tan Christoph Bergmeir AI4TS 42 0 0 08 Aug 2024
Forecasting with Deep Learning: Beyond Average of Average of Average Performance Vítor Cerqueira Luis Roque Carlos Soares 17 1 0 24 Jun 2024
The impact of data set similarity and diversity on transfer learning success in time series forecasting Claudia Ehrig Benedikt Sonnleitner Ursula Neumann Catherine Cleophas Germain Forestier AI4TS 27 0 0 09 Apr 2024
A review of regularised estimation methods and cross-validation in spatiotemporal statistics Philipp Otto A. Fassò Paolo Maranzano 14 0 0 31 Jan 2024
Symbolic Regression as Feature Engineering Method for Machine and Deep Learning Regression Tasks Assaf Shmuel Oren Glickman Teddy Lazebnik 20 9 0 10 Nov 2023
Large Language Models Are Zero-Shot Time Series Forecasters Nate Gruver Marc Finzi Shikai Qiu Andrew Gordon Wilson AI4TS 25 313 0 11 Oct 2023
Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domain Gerald Woo Chenghao Liu Akshat Kumar Doyen Sahoo AI4TS AI4CE 16 12 0 08 Oct 2023
1D-CapsNet-LSTM: A Deep Learning-Based Model for Multi-Step Stock Index Forecasting Cheng Zhang N. N. Sjarif Roslina Ibrahim AIFin AI4TS 10 6 0 03 Oct 2023
Hierarchical learning, forecasting coherent spatio-temporal individual and aggregated building loads J. Leprince H. Madsen J. Møller W. Zeiler 8 1 0 30 Jan 2023
Causal Effect Estimation with Global Probabilistic Forecasting: A Case Study of the Impact of Covid-19 Lockdowns on Energy Demand Ankitha Nandipura Prasanna Priscila Grecov Angela Dieyu Weng Christoph Bergmeir 7 0 0 19 Sep 2022
FRANS: Automatic Feature Extraction for Time Series Forecasting A. Chernikov Chang Wei Tan Pablo Montero-Manso Christoph Bergmeir AI4TS 11 1 0 15 Sep 2022
FreDo: Frequency Domain-based Long-Term Time Series Forecasting Fan-Keng Sun Duane S. Boning AI4TS 45 10 0 24 May 2022
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting Tian Zhou Ziqing Ma Xue Wang Qingsong Wen Liang Sun Tao Yao Wotao Yin Rong Jin AI4TS 112 165 0 18 May 2022
Learning in High Dimension Always Amounts to Extrapolation Randall Balestriero J. Pesenti Yann LeCun 28 87 0 18 Oct 2021
How to avoid machine learning pitfalls: a guide for academic researchers M. Lones VLM FaML OnRL 54 75 0 05 Aug 2021
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting Haoyi Zhou Shanghang Zhang J. Peng Shuai Zhang Jianxin Li Hui Xiong Wan Zhang AI4TS 161 3,799 0 14 Dec 2020