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Time Series Forecasting

22 papers with code · Time Series

Time series forecasting is the task of predicting future values of a time series (as well as uncertainty bounds).

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Latest papers with code

Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters

29 Sep 2019vcerqueira/MLforForecasting

Using a learning curve method, our results suggest that machine learning methods improve their relative predictive performance as the sample size grows.

TIME SERIES TIME SERIES FORECASTING

9
29 Sep 2019

Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models

19 Sep 2019vincent-leguen/STDL

We introduce a differentiable loss function suitable for training deep neural nets, and provide a custom back-prop implementation for speeding up optimization.

TIME SERIES TIME SERIES FORECASTING

15
19 Sep 2019

Real Time Trajectory Prediction Using Deep Conditional Generative Models

9 Sep 2019sebasutp/trajectory_forcasting

Data driven methods for time series forecasting that quantify uncertainty open new important possibilities for robot tasks with hard real time constraints, allowing the robot system to make decisions that trade off between reaction time and accuracy in the predictions.

TIME SERIES TIME SERIES FORECASTING TRAJECTORY PREDICTION

4
09 Sep 2019

Port-Hamiltonian Approach to Neural Network Training

6 Sep 2019Zymrael/PortHamiltonianNN

Neural networks are discrete entities: subdivided into discrete layers and parametrized by weights which are iteratively optimized via difference equations.

TIME SERIES FORECASTING

8
06 Sep 2019

Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions

2 Sep 2019HansikaPH/time-series-forecasting

Recurrent Neural Networks (RNN) have become competitive forecasting methods, as most notably shown in the winning method of the recent M4 competition.

TIME SERIES TIME SERIES FORECASTING

6
02 Sep 2019

Deep Learning for Time Series Forecasting: The Electric Load Case

22 Jul 2019albertogaspar/dts

Management and efficient operations in critical infrastructure such as Smart Grids take huge advantage of accurate power load forecasting which, due to its nonlinear nature, remains a challenging task.

LOAD FORECASTING TIME SERIES FORECASTING

8
22 Jul 2019

Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm

7 Jul 2019damitkwr/ESRNN-GPU

Due to their prevalence, time series forecasting is crucial in multiple domains.

TIME SERIES TIME SERIES FORECASTING

89
07 Jul 2019

GluonTS: Probabilistic Time Series Models in Python

12 Jun 2019awslabs/gluon-ts

We introduce Gluon Time Series (GluonTS, available at https://gluon-ts. mxnet. io), a library for deep-learning-based time series modeling.

ANOMALY DETECTION TIME SERIES TIME SERIES FORECASTING TIME SERIES PREDICTION

686
12 Jun 2019

Probabilistic Forecasting with Temporal Convolutional Neural Network

11 Jun 2019oneday88/kdd2019deepTCN

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

REPRESENTATION LEARNING TIME SERIES TIME SERIES FORECASTING

12
11 Jun 2019

N-BEATS: Neural basis expansion analysis for interpretable time series forecasting

24 May 2019philipperemy/n-beats

We focus on solving the univariate times series point forecasting problem using deep learning.

TIME SERIES TIME SERIES FORECASTING

34
24 May 2019