Gaussian process for long-term time-series forecasting

No abstract is available for this paper.

• Publication year

  2009

• Venue

  2009 International Joint Conference on Neural Networks

• Publication date

  2009-06-14

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1109/IJCNN.2009.5178729
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Nonparametric Statistical Inference

  2020cited by this paper
• Automatic Modelling and Forecasting with Artificial Neural Networks- A forecasting competition evaluation

  2008cited by this paper
• Introduction to Gaussian Processes

  2008cited by this paper
• Time Series Forecasting Using Multiple Gaussian Process Prior Model

  2007cited by this paper
• Methodology for long-term prediction of time series

  2007cited by this paper
• Advances in Gaussian Processes Tutorial at NIPS 2006 in Vancouver

  2006cited by this paper
• Another look at measures of forecast accuracy

  2006cited by this paper
• Gaussian process for nonstationary time series prediction

  2004cited by this paper
• Gaussian Process Priors with Uncertain Inputs - Application to Multiple-Step Ahead Time Series Forecasting

  2002cited by this paper
• A comparison between neural-network forecasting techniques-case study: river flow forecasting

  1999cited by this paper
• Forecasting: Methods and Applications, 3rd Edition

  1998cited by this paper
• In Advances in Neural Information Processing Systems

  1996cited by this paper
• Bayesian learning for neural networks

  1995cited by this paper
• The Analysis of Time Series: An Introduction

  1990cited by this paper
• Curve Fitting and Optimal Design for Prediction

  1978cited by this paper
• On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other

  1947cited by this paper
• Individual Comparisons by Ranking Methods

  1945cited by this paper

• Parallel time-series mixer network enhanced by slicing procedure and attention mechanism for remaining useful life prediction

  2025cites this paper
• Application of machine learning in modeling the quality of acoustic environments: A review

  2025cites this paper
• Efficient Model Selection for Time Series Forecasting via LLMs

  2025cites this paper
• Evaluation-free Time-series Forecasting Model Selection via Meta-learning

  2025cites this paper
• Knowledge-enhanced Transformer for Multivariate Long Sequence Time-series Forecasting

  2024cites this paper
• Predicting the performance of an industrial furnace using Gaussian process and linear regression: A comparison

  2023cites this paper
• Vehicle Motion Prediction Algorithm with Driving Intention Classification

  2022cites this paper
• An Automatic Method of Autoregression Part Selection for Gaussian Time Series Prediction

  2022cites this paper
• AutoForecast: Automatic Time-Series Forecasting Model Selection

  2022cites this paper
• An LSTM‐based approach to precise landing of a UAV on a moving platform

  2022cites this paper
• Predictive Control and Communication Co-Design via Two-Way Gaussian Process Regression and AoI-Aware Scheduling

  2021cites this paper
• Estimation of Stochastic Time Lags between Data Sources in Distributed Production Facilities Based on Cross-Correlated Signals

  2021cites this paper
• Optimized Bayesian adaptive resonance theory mapping model using a rational quadratic kernel and Bayesian quadratic regularization

  2021cites this paper
• Gaussian processes with skewed Laplace spectral mixture kernels for long-term forecasting

  2020cites this paper
• A Hybrid Gaussian Process Approach to Robust Economic Model Predictive Control

  2020cites this paper
• A Review of Deep Learning Models for Time Series Prediction

  2019cites this paper
• Online sales prediction via trend alignment-based multitask recurrent neural networks

  2019cites this paper
• Predicting a Stock Portfolio with the Multivariate Bayesian Structural Time Series Model: Do News or Emotions Matter?

  2019cites this paper
• Residential probabilistic load forecasting: A method using Gaussian process designed for electric load data

  2018influential citation
• TADA: Trend Alignment with Dual-Attention Multi-task Recurrent Neural Networks for Sales Prediction

  2018cites this paper
• Time series forecasting using improved ARIMA

  2016cites this paper
• Gaussian Process Regression for Long-Term Time Series Forecasting

  2016influential citation
• SMiLer: A Semi-Lazy Time Series Prediction System for Sensors

  2015cites this paper
• Multistep Ahead Groundwater Level Time-Series Forecasting Using Gaussian Process Regression and ANFIS

  2015cites this paper
• Predicting car states through learned models of vehicle dynamics and user behaviours

  2015cites this paper
• A Novel Time Series Prediction Approach Based on a Hybridization of Least Squares Support Vector Regression and Swarm Intelligence

  2014cites this paper
• Elasticity in IaaS Cloud, preserving performance SLAs

  2014cites this paper
• Model-based transmission reduction and virtual sensing in wireless sensor networks

  2013cites this paper
• FRASel: a consensus of feature ranking methods for time series modelling

  2012cites this paper