Time Series Regression

26 papers with code • 0 benchmarks • 2 datasets

Predicting one or more scalars for an entire time series example.

Most implemented papers

A Transformer-based Framework for Multivariate Time Series Representation Learning

gzerveas/mvts_transformer 6 Oct 2020

In this work we propose for the first time a transformer-based framework for unsupervised representation learning of multivariate time series.

A Multi-Horizon Quantile Recurrent Forecaster

tianchen101/MQRNN 29 Nov 2017

We propose a framework for general probabilistic multi-step time series regression.

Monash University, UEA, UCR Time Series Extrinsic Regression Archive

ChangWeiTan/TSRegression 19 Jun 2020

We refer to this problem as Time Series Extrinsic Regression (TSER), where we are interested in a more general methodology of predicting a single continuous value, from univariate or multivariate time series.

Changepoint Detection in Noisy Data Using a Novel Residuals Permutation-Based Method (RESPERM): Benchmarking and Application to Single Trial ERPs

gkonczak/chp.perm Brain sciences 2022

Here, we present a new method for detecting a single changepoint in a linear time series regression model, termed residuals permutation-based method (RESPERM).

Multiobjective Programming for Type-2 Hierarchical Fuzzy Inference Trees

vojha-code/Hierarchical-Fuzzy-Tree 16 May 2017

Hence, the proposed HFIT is an efficient and competitive alternative to the other FISs for function approximation and feature selection.

Ensemble of heterogeneous flexible neural trees using multiobjective genetic programming

vojha-code/Neural-Tree-Software 16 May 2017

Machine learning algorithms are inherently multiobjective in nature, where approximation error minimization and model's complexity simplification are two conflicting objectives.

Deconvolutional Time Series Regression: A Technique for Modeling Temporally Diffuse Effects

coryshain/dtsr EMNLP 2018

Researchers in computational psycholinguistics frequently use linear models to study time series data generated by human subjects.

High-Dimensional Granger Causality Tests with an Application to VIX and News

jstriaukas/midasml 13 Dec 2019

We establish the debiased central limit theorem for low dimensional groups of regression coefficients and study the HAC estimator of the long-run variance based on the sparse-group LASSO residuals.

Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows

EmoryMLIP/DOvsOD_NeuralODEs 27 May 2020

Neural ODEs are ordinary differential equations (ODEs) with neural network components.

Time Series Extrinsic Regression

ChangWeiTan/TSRegression 23 Jun 2020

This paper studies Time Series Extrinsic Regression (TSER): a regression task of which the aim is to learn the relationship between a time series and a continuous scalar variable; a task closely related to time series classification (TSC), which aims to learn the relationship between a time series and a categorical class label.