This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time series forecasting research space.

Overview

TSForecasting

This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time series forecasting research space.

The benchmark datasets are available at: https://zenodo.org/communities/forecasting. For more details, please refer to our website: https://forecastingdata.org/ and paper: https://arxiv.org/abs/2105.06643.

All datasets contain univariate time series and they are availble in a new format that we name as .tsf, pioneered by the sktime .ts format. The data can be loaded into the R environment in tsibble format [1] by following the example in "utils/data_loader.R". It uses a similar approach to the arff file loading method in R foreign package [2]. The data can be loaded into the Python environment as a Pandas dataframe by following the example in "utils/data_loader.py". Download the .tsf files as required from our Zenodo dataset repository and put them into "tsf_data" folder.

The fixed horizon, rolling origin and feature calculation related experiments are there in the "experiments" folder. Please see the examples in the corresponding R scripts in the "experiments" folder for more details. Makesure to create a folder named "results" in the parent level and sub-folders as necessary before running the experiments. The outputs of the experiments will be stored into the sub-folders within the "results" folder as mentioned follows:

Sub-folder Name Stored Output
rolling_origin_forecasts rolling origin forecasts
rolling_origin_errors rolling origin errors
rolling_origin_execution_times rolling origin execution times
fixed_horizon_forecasts fixed horizon forecasts
fixed_horizon_errors fixed horizon errors
fixed_horizon_execution_times fixed horizon execution times
tsfeatures tsfeatures
catch22_features catch22 features
lambdas boxcox lambdas

Citing Our Work

When using this repository, please cite:

@misc{godahewa2021monash,
    author="Godahewa, Rakshitha and Bergmeir, Christoph and Webb, Geoffrey I. and Hyndman, Rob J. and Montero-Manso, Pablo",
    title="Monash Time Series Forecasting Archive",
    howpublished ="\url{https://arxiv.org/abs/2105.06643}",
    year="2021"
}

References

[1] Wang, E., Cook, D., Hyndman, R. J. (2020). A new tidy data structure to support exploration and modeling of temporal data. Journal of Computational and Graphical Statistics. doi:10.1080/10618600.2019.1695624.

[2] R Core Team (2018). foreign: Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', 'dBase', .... R package version 0.8-71. https://CRAN.R-project.org/package=foreign

Owner
Rakshitha Godahewa
PhD Student
Rakshitha Godahewa
Deep Learning Visuals contains 215 unique images divided in 23 categories

Deep Learning Visuals contains 215 unique images divided in 23 categories (some images may appear in more than one category). All the images were originally published in my book "Deep Learning with P

Daniel Voigt Godoy 1.3k Dec 28, 2022
PyTorch implementation of the Value Iteration Networks (VIN) (NIPS '16 best paper)

Value Iteration Networks in PyTorch Tamar, A., Wu, Y., Thomas, G., Levine, S., and Abbeel, P. Value Iteration Networks. Neural Information Processing

LEI TAI 75 Nov 24, 2022
XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale

XtremeDistilTransformers for Distilling Massive Multilingual Neural Networks ACL 2020 Microsoft Research [Paper] [Video] Releasing [XtremeDistilTransf

Microsoft 125 Jan 04, 2023
Frequency Spectrum Augmentation Consistency for Domain Adaptive Object Detection

Frequency Spectrum Augmentation Consistency for Domain Adaptive Object Detection Main requirements torch = 1.0 torchvision = 0.2.0 Python 3 Environm

15 Apr 04, 2022
Optical machine for senses sensing using speckle and deep learning

# Senses-speckle [Remote Photonic Detection of Human Senses Using Secondary Speckle Patterns](https://doi.org/10.21203/rs.3.rs-724587/v1) paper Python

Zeev Kalyuzhner 0 Sep 26, 2021
Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning"

Prompt-Tuning Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning" Currently, we support the following huggigface models: Bart

Andrew Zeng 36 Dec 19, 2022
An updated version of virtual model making

Model-Swap-Face v2   这个项目是基于stylegan2 pSp制作的,比v1版本Model-Swap-Face在推理速度和图像质量上有一定提升。主要的功能是将虚拟模特进行环球不同区域的风格转换,目前转换器提供西欧模特、东亚模特和北非模特三种主流的风格样式,可帮我们实现生产资料零成

seeprettyface.com 62 Dec 09, 2022
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend

Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto

Guillaume Chevalier 103 Jul 22, 2022
🗺 General purpose U-Network implemented in Keras for image segmentation

TF-Unet General purpose U-Network implemented in Keras for image segmentation Getting started • Training • Evaluation Getting started Looking for Jupy

Or Fleisher 2 Aug 31, 2022
Collapse by Conditioning: Training Class-conditional GANs with Limited Data

Collapse by Conditioning: Training Class-conditional GANs with Limited Data Moha

Mohamad Shahbazi 33 Dec 06, 2022
TensorFlow implementation of ENet, trained on the Cityscapes dataset.

segmentation TensorFlow implementation of ENet (https://arxiv.org/pdf/1606.02147.pdf) based on the official Torch implementation (https://github.com/e

Fredrik Gustafsson 248 Dec 16, 2022
REBEL: Relation Extraction By End-to-end Language generation

REBEL: Relation Extraction By End-to-end Language generation This is the repository for the Findings of EMNLP 2021 paper REBEL: Relation Extraction By

Babelscape 222 Jan 06, 2023
Solutions and questions for AoC2021. Merry christmas!

Advent of Code 2021 Merry christmas! 🎄 🎅 To get solutions and approximate execution times for implementations, please execute the run.py script in t

Wilhelm Ågren 5 Dec 29, 2022
This repository is the offical Pytorch implementation of ContextPose: Context Modeling in 3D Human Pose Estimation: A Unified Perspective (CVPR 2021).

Context Modeling in 3D Human Pose Estimation: A Unified Perspective (CVPR 2021) Introduction This repository is the offical Pytorch implementation of

37 Nov 21, 2022
GT4SD, an open-source library to accelerate hypothesis generation in the scientific discovery process.

The GT4SD (Generative Toolkit for Scientific Discovery) is an open-source platform to accelerate hypothesis generation in the scientific discovery process. It provides a library for making state-of-t

Generative Toolkit 4 Scientific Discovery 142 Dec 24, 2022
UMich 500-Level Mobile Robotics Course

MOBILE ROBOTICS: METHODS & ALGORITHMS - WINTER 2022 University of Michigan - NA 568/EECS 568/ROB 530 For slides, lecture notes, and example codes, see

393 Dec 29, 2022
PyTorch implementations of Generative Adversarial Networks.

This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as

Erik Linder-Norén 13.4k Jan 08, 2023
A object detecting neural network powered by the yolo architecture and leveraging the PyTorch framework and associated libraries.

Yolo-Powered-Detector A object detecting neural network powered by the yolo architecture and leveraging the PyTorch framework and associated libraries

Luke Wilson 1 Dec 03, 2021
PyTorch implementation of ENet

PyTorch-ENet PyTorch (v1.1.0) implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation, ported from the lua-torc

David Silva 333 Dec 29, 2022
ExCon: Explanation-driven Supervised Contrastive Learning

ExCon: Explanation-driven Supervised Contrastive Learning Contributors of this repo: Zhibo Zhang ( Zhibo (Darren) Zhang 18 Nov 01, 2022