Multivariate Time Series Forecasting

52 papers with code • 7 benchmarks • 8 datasets

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Use these libraries to find Multivariate Time Series Forecasting models and implementations

Most implemented papers

Neural Ordinary Differential Equations

rtqichen/torchdiffeq NeurIPS 2018

Instead of specifying a discrete sequence of hidden layers, we parameterize the derivative of the hidden state using a neural network.

Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

laiguokun/LSTNet 21 Mar 2017

Multivariate time series forecasting is an important machine learning problem across many domains, including predictions of solar plant energy output, electricity consumption, and traffic jam situation.

DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks

jdb78/pytorch-forecasting 13 Apr 2017

Probabilistic forecasting, i. e. estimating the probability distribution of a time series' future given its past, is a key enabler for optimizing business processes.

Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

liyaguang/DCRNN ICLR 2018

Spatiotemporal forecasting has various applications in neuroscience, climate and transportation domain.

Latent ODEs for Irregularly-Sampled Time Series

YuliaRubanova/latent_ode 8 Jul 2019

Time series with non-uniform intervals occur in many applications, and are difficult to model using standard recurrent neural networks (RNNs).

Recurrent Neural Networks for Multivariate Time Series with Missing Values

PeterChe1990/GRU-D 6 Jun 2016

Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values.

Predictive Business Process Monitoring with LSTM Neural Networks

verenich/ProcessSequencePrediction 7 Dec 2016

First, we show that LSTMs outperform existing techniques to predict the next event of a running case and its timestamp.

Probabilistic Forecasting with Temporal Convolutional Neural Network

ashishpatel26/tcn-keras-Examples 11 Jun 2019

We present a probabilistic forecasting framework based on convolutional neural network for multiple related time series forecasting.

BRITS: Bidirectional Recurrent Imputation for Time Series

caow13/BRITS NeurIPS 2018

It is ubiquitous that time series contains many missing values.

Temporal Pattern Attention for Multivariate Time Series Forecasting

gantheory/TPA-LSTM 12 Sep 2018

To obtain accurate prediction, it is crucial to model long-term dependency in time series data, which can be achieved to some good extent by recurrent neural network (RNN) with attention mechanism.