Time Series Forecasting

Time series forecasting aims to predict future values based on historical data, crucial for diverse applications from finance to healthcare. Current research emphasizes improving model accuracy and efficiency, focusing on transformer-based architectures, state-space models like Mamba, and hybrid approaches combining their strengths, as well as exploring data augmentation and explainable AI techniques. These advancements are driving improvements in forecasting accuracy and interpretability, leading to better decision-making across various sectors and contributing to a deeper understanding of complex temporal dynamics.

Papers

May 11, 2022

Efficient Automated Deep Learning for Time Series Forecasting
Difan Deng, Florian Karl, Frank Hutter, Bernd Bischl, Marius Lindauer
Time Series Forecasting Neural Architecture Multi Fidelity Automated Deep Learning Neural Architecture Search Space

April 28, 2022

Autoencoder based Hybrid Multi-Task Predictor Network for Daily Open-High-Low-Close Prices Prediction of Indian Stocks
Debasrita Chakraborty, Susmita Ghosh, Ashish Ghosh
Long Short Term Memory Supervised Autoencoder Multi Task Time Series Forecasting Indian Stock Market Stock Movement Prediction Standard LSTM Stock Price Price Movement

April 23, 2022

Time Series Forecasting (TSF) Using Various Deep Learning Models
Jimeng Shi, Mahek Jain, Giri Narasimhan
Deep Learning Deep Learning Model Time Series Forecasting LSTM Network Predictive Model Step Prediction Time Series Forecasting Model

April 7, 2022

Few-Shot Forecasting of Time-Series with Heterogeneous Channels
Lukas Brinkmeyer, Rafael Rego Drumond, Johannes Burchert, Lars Schmidt-Thieme
Time Series Time Series Forecasting Multivariate Time Series State of the Art Forecasting Shot Classification Heterogeneous Wireless Shot Forecasting

April 1, 2022

Physics Informed Shallow Machine Learning for Wind Speed Prediction
Daniele Lagomarsino-Oneto, Giacomo Meanti, Nicolò Pagliana, Alessandro Verri, Andrea Mazzino, Lorenzo Rosasco, Agnese Seminara
Time Series Forecasting Supervised Learning Physic Informed Machine Learning Data Driven Approach Weather Forecasting Wind Speed Prediction Horizon

March 26, 2022

AutoTS: Automatic Time Series Forecasting Model Design Based on Two-Stage Pruning
Chunnan Wang, Xingyu Chen, Chengyue Wu, Hongzhi Wang
Time Series Time Series Forecasting Progressive Pruning Time Series Forecasting Model

March 18, 2022

Performance of Deep Learning models with transfer learning for multiple-step-ahead forecasts in monthly time series
Martín Solís, Luis-Alexander Calvo-Valverde
Deep Learning Deep Learning Model Transfer Learning Time Series System Performance Time Series Forecasting LSTM Network Formality Transfer Multi Step

March 17, 2022

March 15, 2022

DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting
Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu
Time Series Time Series Forecasting Periodic Phenomenon Periodicity Detection

March 14, 2022

A Comparative Study on Forecasting of Retail Sales
Md Rashidul Hasan, Muntasir A Kabir, Rezoan A Shuvro, Pankaz Das
Comparative Study Time Series Forecasting E Commerce State of the Art Forecasting Forecasting Model Integrated Moving Average Retail Store

March 11, 2022

Dual reparametrized Variational Generative Model for Time-Series Forecasting
Ziang Chen
Variational Autoencoder Time Series Forecasting Latent Vector Dual System Variational Generative Model Temporal Inference Variational Density

March 9, 2022

Monitoring Time Series With Missing Values: a Deep Probabilistic Approach
Oshri Barazani, David Tolpin
Time Series Time Series Forecasting Multivariate Time Series Time Series Prediction Missing Value High Dimensional Time Series Deep Probabilistic Model

March 7, 2022

Automated Few-Shot Time Series Forecasting based on Bi-level Programming
Jiangjiao Xu, Ke Li
Time Series Forecasting Hyperparameter Optimization Bilevel Optimization Time Series Prediction Renewable Energy

March 2, 2022

Boosted Ensemble Learning based on Randomized NNs for Time Series Forecasting
Grzegorz Dudek
Time Series Forecasting Ensemble Learning Forecasting Task Boosting Ensemble

February 27, 2022

ONE-NAS: An Online NeuroEvolution based Neural Architecture Search for Time Series Forecasting
Zimeng Lyu, Travis Desell
Recurrent Neural Network Neural Architecture Search Time Series Forecasting Wind Power SEMI SuperYOLO Na Hardware Accelerated NeuroEvolution

February 23, 2022

A Differential Attention Fusion Model Based on Transformer for Time Series Forecasting
Benhan Li, Shengdong Du, Tianrui Li
Transformer Based Transformer Architecture Time Series Forecasting LSTM Network Time Dependent Feature

February 22, 2022

Combating Distribution Shift for Accurate Time Series Forecasting via Hypernetworks
Wenying Duan, Xiaoxi He, Lu Zhou, Lothar Thiele, Hong Rao
Time Series Time Series Forecasting Distribution Shift Attention Hypernetworks Real World Time Series

February 17, 2022

Multi-Objective Model Selection for Time Series Forecasting
Oliver Borchert, David Salinas, Valentin Flunkert, Tim Januschowski, Stephan Günnemann
Time Series Forecasting Multi Objective Forecasting Model Univariate Time Series Forecasting Forecasting Method

February 8, 2022

KENN: Enhancing Deep Neural Networks by Leveraging Knowledge for Time Series Forecasting
Muhammad Ali Chattha, Ludger van Elst, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed
Deep Neural Network Time Series Time Series Forecasting Knowledge Based State of the Art Forecasting Natural Disaster Knowledge Fusion Knowledge Enhanced