About

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

Benchmarks

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Datasets

Latest papers with code

Evaluation of deep learning models for multi-step ahead time series prediction

26 Mar 2021sydney-machine-learning/deeplearning_timeseries

Our deep learning methods compromise of simple recurrent neural networks, long short term memory (LSTM) networks, bidirectional LSTM, encoder-decoder LSTM networks, and convolutional neural networks.

 Ranked #1 on Time Series Prediction on Sunspot (using extra training data)

TIME SERIES TIME SERIES PREDICTION

3
26 Mar 2021

Dynamic Virtual Graph Significance Networks for Predicting Influenza

16 Feb 2021aI-area/DVGSN

In this study, we develop a novel method, Dynamic Virtual Graph Significance Networks (DVGSN), which can supervisedly and dynamically learn from similar "infection situations" in historical timepoints.

REPRESENTATION LEARNING TIME SERIES TIME SERIES PREDICTION

0
16 Feb 2021

Graph Edit Networks

ICLR 2021 bpaassen/graph-edit-networks

With this result, we hope to provide a firm theoretical basis for a next generation of time series prediction models.

GRAPH GENERATION LINK PREDICTION TIME SERIES TIME SERIES PREDICTION

0
01 Jan 2021

Recursive Tree Grammar Autoencoders

3 Dec 2020bpaassen/rtgae

Machine learning on tree data has been mostly focused on trees as input.

DRUG DISCOVERY TIME SERIES TIME SERIES PREDICTION

0
03 Dec 2020

ATCN: Agile Temporal Convolutional Networks for Processing of Time Series on Edge

10 Nov 2020TeCSAR-UNCC/ATCN

It makes fundamental improvements over the mainstream temporal convolutional neural networks, including the incorporation of separable depth-wise convolution to reduce the computational complexity of the model and residual connections as time attention machines, increase the network depth and accuracy.

GENERAL CLASSIFICATION HEARTBEAT CLASSIFICATION TIME SERIES TIME SERIES PREDICTION

3
10 Nov 2020

Deep Switching Auto-Regressive Factorization:Application to Time Series Forecasting

10 Sep 2020ostadabbas/DSARF

We introduce deep switching auto-regressive factorization (DSARF), a deep generative model for spatio-temporal data with the capability to unravel recurring patterns in the data and perform robust short- and long-term predictions.

TIME SERIES TIME SERIES FORECASTING TIME SERIES PREDICTION VARIATIONAL INFERENCE WEATHER FORECASTING

10
10 Sep 2020

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

NeurIPS 2020 benedekrozemberczki/pytorch_geometric_temporal

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.

GRAPH GENERATION MULTIVARIATE TIME SERIES FORECASTING SPATIO-TEMPORAL FORECASTING TIME SERIES TIME SERIES PREDICTION TRAFFIC PREDICTION

687
06 Jul 2020

Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning

23 Jun 2020anhtuan5696/TPAMTL

Existing asymmetric multi-task learning methods tackle this negative transfer problem by performing knowledge transfer from tasks with low loss to tasks with high loss.

KNOWLEDGE GRAPHS MULTI-TASK LEARNING TIME SERIES TIME SERIES PREDICTION

6
23 Jun 2020

Low-Rank Autoregressive Tensor Completion for Multivariate Time Series Forecasting

18 Jun 2020xinychen/tensor-learning

In this paper, we propose a low-rank autoregressive tensor completion (LATC) framework to model multivariate time series data.

IMPUTATION MULTIVARIATE TIME SERIES FORECASTING TIME SERIES TIME SERIES PREDICTION

90
18 Jun 2020

Reservoir Computing meets Recurrent Kernels and Structured Transforms

NeurIPS 2020 rubenohana/Reservoir-computing-kernels

Reservoir Computing is a class of simple yet efficient Recurrent Neural Networks where internal weights are fixed at random and only a linear output layer is trained.

TIME SERIES TIME SERIES PREDICTION

2
12 Jun 2020