Time Series Prediction

107 papers with code • 2 benchmarks • 11 datasets

The goal of Time Series Prediction is to infer the future values of a time series from the past.

Source: Orthogonal Echo State Networks and stochastic evaluations of likelihoods

Libraries

Use these libraries to find Time Series Prediction models and implementations

Most implemented papers

Liquid Time-constant Networks

raminmh/liquid_time_constant_networks 8 Jun 2020

We introduce a new class of time-continuous recurrent neural network models.

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

LeiBAI/AGCRN NeurIPS 2020

We further propose an Adaptive Graph Convolutional Recurrent Network (AGCRN) to capture fine-grained spatial and temporal correlations in traffic series automatically based on the two modules and recurrent networks.

Recursive Tree Grammar Autoencoders

bpaassen/rtgae 3 Dec 2020

Machine learning on trees has been mostly focused on trees as input to algorithms.

Autoregressive Convolutional Recurrent Neural Network for Univariate and Multivariate Time Series Prediction

xinzezhang/timeseriesforecasting-torch 6 Mar 2019

Time Series forecasting (univariate and multivariate) is a problem of high complexity due the different patterns that have to be detected in the input, ranging from high to low frequencies ones.

Time Series Modeling for Dream Team in Fantasy Premier League

JoshuaPlacidi/Fantasy-Football-Team-Predictions 19 Sep 2019

The performance of football players in English Premier League varies largely from season to season and for different teams.

Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks

abr/neurips2019 NeurIPS 2019

Backpropagation through the ODE solver allows each layer to adapt its internal time-step, enabling the network to learn task-relevant time-scales.

From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction

helange23/from_fourier_to_koopman 1 Apr 2020

We propose spectral methods for long-term forecasting of temporal signals stemming from linear and nonlinear quasi-periodic dynamical systems.

Tree Echo State Autoencoders with Grammars

bpaassen/tree_echo_state_autoencoders 19 Apr 2020

Tree data occurs in many forms, such as computer programs, chemical molecules, or natural language.

COVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMF

HanbaekLyu/ONMF-COVID19 20 Apr 2020

One of the main sources of difficulty is that a very limited amount of daily COVID-19 case data is available, and with few exceptions, the majority of countries are currently in the "exponential spread stage," and thus there is scarce information available which would enable one to predict the phase transition between spread and containment.