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Datasets

Greatest papers with code

Neural Ordinary Differential Equations

NeurIPS 2018 rtqichen/torchdiffeq

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

LATENT VARIABLE MODELS MULTIVARIATE TIME SERIES FORECASTING MULTIVARIATE TIME SERIES IMPUTATION

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

14 Dec 2020zhouhaoyi/Informer2020

Many real-world applications require the prediction of long sequence time-series, such as electricity consumption planning.

MULTIVARIATE TIME SERIES FORECASTING TIME SERIES UNIVARIATE TIME SERIES FORECASTING

Low-Rank Autoregressive Tensor Completion for Multivariate Time Series Forecasting

18 Jun 2020xinychen/transdim

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

Temporal Pattern Attention for Multivariate Time Series Forecasting

12 Sep 2018gantheory/TPA-LSTM

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.

MULTIVARIATE TIME SERIES FORECASTING TIME SERIES

FlowDB a large scale precipitation, river, and flash flood dataset

21 Dec 2020AIStream-Peelout/flow-forecast

We introduce a novel hourly river flow and precipitation dataset and a second subset of flash flood events with damage estimates and injury counts.

MULTIVARIATE TIME SERIES FORECASTING

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

21 Mar 2017laiguokun/LSTNet

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.

MULTIVARIATE TIME SERIES FORECASTING TIME SERIES

Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting

28 Jan 2021zalandoresearch/pytorch-ts

In this work, we propose \texttt{TimeGrad}, an autoregressive model for multivariate probabilistic time series forecasting which samples from the data distribution at each time step by estimating its gradient.

LATENT VARIABLE MODELS MULTIVARIATE TIME SERIES FORECASTING PROBABILISTIC TIME SERIES FORECASTING TIME SERIES

Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows

ICLR 2021 zalandoresearch/pytorch-ts

In this work we model the multivariate temporal dynamics of time series via an autoregressive deep learning model, where the data distribution is represented by a conditioned normalizing flow.

DECISION MAKING MULTIVARIATE TIME SERIES FORECASTING PROBABILISTIC DEEP LEARNING PROBABILISTIC TIME SERIES FORECASTING TIME SERIES

Latent ODEs for Irregularly-Sampled Time Series

8 Jul 2019YuliaRubanova/latent_ode

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

MULTIVARIATE TIME SERIES FORECASTING MULTIVARIATE TIME SERIES IMPUTATION TIME SERIES TIME SERIES CLASSIFICATION