Forecasting Model

Time series forecasting models aim to predict future values based on historical data, a crucial task across diverse fields from finance and energy to healthcare and environmental science. Current research emphasizes improving accuracy and robustness through advanced architectures like transformers, recurrent neural networks (RNNs, including LSTMs), and hybrid models combining machine learning with statistical methods, often incorporating external data sources like news or market indicators to enhance predictive power. These advancements are significant because accurate forecasting enables better resource allocation, risk management, and informed decision-making in various sectors, ultimately leading to improved efficiency and outcomes.

Papers

February 4, 2024

Minusformer: Improving Time Series Forecasting by Progressively Learning Residuals
Daojun Liang, Haixia Zhang, Dongfeng Yuan, Bingzheng Zhang, Minggao Zhang
Time Series Forecasting Ensemble Learning Model Overfitting Forecasting Model

January 30, 2024

Addressing Distribution Shift in Time Series Forecasting with Instance Normalization Flows
Wei Fan, Shun Zheng, Pengyang Wang, Rui Xie, Jiang Bian, Yanjie Fu
Time Series Forecasting Distribution Shift Forecasting Model Instance Normalization Time Series Transformer Distribution Shift Problem Forecasting Architecture

December 18, 2023

ShuttleSHAP: A Turn-Based Feature Attribution Approach for Analyzing Forecasting Models in Badminton
Wei-Yao Wang, Wen-Chih Peng, Wei Wang, Philip S. Yu
Forecasting Model Feature Attribution Method Player Performance Autonomous Shuttle Badminton Report Player Behavior Turn Based Multi Agent Prediction

November 19, 2023

SPLAIN: Augmenting Cybersecurity Warnings with Reasons and Data
Vera A. Kazakova, Jena D. Hwang, Bonnie J. Dorr, Yorick Wilks, J. Blake Gage, Alex Memory, Mark A. Clark
Raw Data Reason Giving Forecasting Model Threat Detection Cyber Threat

November 10, 2023

Forte: An Interactive Visual Analytic Tool for Trust-Augmented Net Load Forecasting
Kaustav Bhattacharjee, Soumya Kundu, Indrasis Chakraborty, Aritra Dasgupta
Forecasting Model Interventional Data Visual Analytics Tool Net Load Forecasting

November 5, 2023

An adaptive standardisation methodology for Day-Ahead electricity price forecasting
Carlos Sebastián, Carlos E. González-Guillén, Jesús Juan
Time Series Forecasting Forecasting Model Electricity Market Data Standardization Dataset Shift Day Ahead

October 28, 2023

Explainable Modeling for Wind Power Forecasting: A Glass-Box Approach with High Accuracy
Wenlong Liao, Fernando Porte-Agel, Jiannong Fang, Birgitte Bak-Jensen, Guangchun Ruan, Zhe Yang
Forecasting Model Explainable Model High Accuracy Wind Power Forecasting Glass Box

October 14, 2023

A decoder-only foundation model for time-series forecasting
Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou
Large Language Model Natural Language Processing Large Corpus Forecasting Model Time Series Foundation Model Decoder Only Architecture

October 12, 2023

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
Kashif Rasul, Arjun Ashok, Andrew Robert Williams, Hena Ghonia, Rishika Bhagwatkar, Arian Khorasani, Mohammad Javad Darvishi Bayazi, George Adamopoulos, Roland Riachi, Nadhir Hassen, Marin Biloš, Sahil Garg, Anderson Schneider, Nicolas Chapados, Alexandre Drouin, Valentina Zantedeschi, Yuriy Nevmyvaka, Irina Rish
Foundation Model Time Series Forecasting Time Series Data Forecasting Model Probabilistic Time Series Forecasting

September 11, 2023

Quantitative Analysis of Forecasting Models:In the Aspect of Online Political Bias
Srinath Sai Tripuraneni, Sadia Kamal, Arunkumar Bagavathi
Social Medium Forecasting Model Political Bias Quantitative Analysis Elusive Aspect Online Social Medium

September 7, 2023

A Natural Gas Consumption Forecasting System for Continual Learning Scenarios based on Hoeffding Trees with Change Point Detection Mechanism
Radek Svoboda, Sebastian Basterrech, Jędrzej Kozal, Jan Platoš, Michał Woźniak
Change Point Detection Forecasting Model Continual Learning Scenario Robust Forecasting Forecast Error Hoeffding Tree

September 4, 2023

A Blackbox Model Is All You Need to Breach Privacy: Smart Grid Forecasting Models as a Use Case
Hussein Aly, Abdulaziz Al-Ali, Abdullah Al-Ali, Qutaibah Malluhi
Long Short Term Memory Black Box Model Load Forecasting Smart Grid Use Case Forecasting Model Privacy Breach

August 31, 2023

Forecasting Emergency Department Crowding with Advanced Machine Learning Models and Multivariable Input
Jalmari Tuominen, Eetu Pulkkinen, Jaakko Peltonen, Juho Kanniainen, Niku Oksala, Ari Palomäki, Antti Roine
Electronic Health Record Forecasting Model Demand Prediction Variable Model Advanced Machine Learning Forecasting Analysis

August 16, 2023

LSTM-Based Forecasting Model for GRACE Accelerometer Data
Neda Darbeheshti, Elahe Moradi
Forecasting Model Accelerometer Data Gravity Compensation Gravity Informed

July 14, 2023

Benchmarks and Custom Package for Electrical Load Forecasting
Zhixian Wang, Qingsong Wen, Chaoli Zhang, Liang Sun, Leandro Von Krannichfeldt, Yi Wang
New Benchmark Load Forecasting Forecasting Model SPR Package

May 11, 2023

A Generic Approach to Integrating Time into Spatial-Temporal Forecasting via Conditional Neural Fields
Minh-Thanh Bui, Duc-Thinh Ngo, Demin Lu, Zonghua Zhang
Forecasting Model Spatio Temporal Forecasting Autoregressive Neural Network Forecasting Algorithm Efficient Time Series Forecasting Conditional Neural Field Driving Network Long Time Integration

April 13, 2023

Streamlined Framework for Agile Forecasting Model Development towards Efficient Inventory Management
Jonathan Hans Soeseno, Sergio González, Trista Pei-Chun Chen
Time Series Data Cross Validation Robust Training Forecasting Model Inventory Management Forecasting Competition Visual Forecasting Streamlined Approach

April 11, 2023

The Capacity and Robustness Trade-off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting
Lu Han, Han-Jia Ye, De-Chuan Zhan
Multivariate Time Series Multivariate Time Series Forecasting Multivariate Time Series Data Forecasting Model Capacity Loss Multivariate Forecasting Robustness Trade

March 13, 2023

Model scale versus domain knowledge in statistical forecasting of chaotic systems
William Gilpin
Domain Knowledge Long Horizon Chaotic System Predictability Problem Forecasting Model Model Scale

February 16, 2023

Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models
Guillaume Lambert, Bachir Hamrouche, Joseph de Vilmarest
Human Prediction Forecasting Model Additive Model Day Ahead Adaptive Model Electricity Load

Forecasting Model

Papers

Minusformer: Improving Time Series Forecasting by Progressively Learning Residuals

Addressing Distribution Shift in Time Series Forecasting with Instance Normalization Flows

ShuttleSHAP: A Turn-Based Feature Attribution Approach for Analyzing Forecasting Models in Badminton

SPLAIN: Augmenting Cybersecurity Warnings with Reasons and Data

Forte: An Interactive Visual Analytic Tool for Trust-Augmented Net Load Forecasting

An adaptive standardisation methodology for Day-Ahead electricity price forecasting

Explainable Modeling for Wind Power Forecasting: A Glass-Box Approach with High Accuracy

A decoder-only foundation model for time-series forecasting

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Quantitative Analysis of Forecasting Models:In the Aspect of Online Political Bias

A Natural Gas Consumption Forecasting System for Continual Learning Scenarios based on Hoeffding Trees with Change Point Detection Mechanism

A Blackbox Model Is All You Need to Breach Privacy: Smart Grid Forecasting Models as a Use Case

Forecasting Emergency Department Crowding with Advanced Machine Learning Models and Multivariable Input

LSTM-Based Forecasting Model for GRACE Accelerometer Data

Benchmarks and Custom Package for Electrical Load Forecasting

A Generic Approach to Integrating Time into Spatial-Temporal Forecasting via Conditional Neural Fields

Streamlined Framework for Agile Forecasting Model Development towards Efficient Inventory Management

The Capacity and Robustness Trade-off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting

Model scale versus domain knowledge in statistical forecasting of chaotic systems

Frugal day-ahead forecasting of multiple local electricity loads by aggregating adaptive models