LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION

Overview

Query Selector

Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sparse attention Transformer algorithm that is especially suitable for long term time series forecasting

Depencency

Python            3.7.9
deepspeed         0.4.0
numpy             1.20.3
pandas            1.2.4
scipy             1.6.3
tensorboardX      1.8
torch             1.7.1
torchaudio        0.7.2
torchvision       0.8.2
tqdm              4.61.0

Results on ETT dataset

Univariate

Data Prediction len Informer MSE Informer MAE Trans former MSE Trans former MAE Query Selector MSE Query Selector MAE MSE ratio
ETTh1 24 0.0980 0.2470 0.0548 0.1830 0.0436 0.1616 0.445
ETTh1 48 0.1580 0.3190 0.0740 0.2144 0.0721 0.2118 0.456
ETTh1 168 0.1830 0.3460 0.1049 0.2539 0.0935 0.2371 0.511
ETTh1 336 0.2220 0.3870 0.1541 0.3201 0.1267 0.2844 0.571
ETTh1 720 0.2690 0.4350 0.2501 0.4213 0.2136 0.3730 0.794
ETTh2 24 0.0930 0.2400 0.0999 0.2479 0.0843 0.2239 0.906
ETTh2 48 0.1550 0.3140 0.1218 0.2763 0.1117 0.2622 0.721
ETTh2 168 0.2320 0.3890 0.1974 0.3547 0.1753 0.3322 0.756
ETTh2 336 0.2630 0.4170 0.2191 0.3805 0.2088 0.3710 0.794
ETTh2 720 0.2770 0.4310 0.2853 0.4340 0.2585 0.4130 0.933
ETTm1 24 0.0300 0.1370 0.0143 0.0894 0.0139 0.0870 0.463
ETTm1 48 0.0690 0.2030 0.0328 0.1388 0.0342 0.1408 0.475
ETTm1 96 0.1940 0.2030 0.0695 0.2085 0.0702 0.2100 0.358
ETTm1 288 0.4010 0.5540 0.1316 0.2948 0.1548 0.3240 0.328
ETTm1 672 0.5120 0.6440 0.1728 0.3437 0.1735 0.3427 0.338

Multivariate

Data Prediction len Informer MSE Informer MAE Trans former MSE Trans former MAE Query Selector MSE Query Selector MAE MSE ratio
ETTh1 24 0.5770 0.5490 0.4496 0.4788 0.4226 0.4627 0.732
ETTh1 48 0.6850 0.6250 0.4668 0.4968 0.4581 0.4878 0.669
ETTh1 168 0.9310 0.7520 0.7146 0.6325 0.6835 0.6088 0.734
ETTh1 336 1.1280 0.8730 0.8321 0.7041 0.8503 0.7039 0.738
ETTh1 720 1.2150 0.8960 1.1080 0.8399 1.1150 0.8428 0.912
ETTh2 24 0.7200 0.6650 0.4237 0.5013 0.4124 0.4864 0.573
ETTh2 48 1.4570 1.0010 1.5220 0.9488 1.4074 0.9317 0.966
ETTh2 168 3.4890 1.5150 1.6225 0.9726 1.7385 1.0125 0.465
ETTh2 336 2.7230 1.3400 2.6617 1.2189 2.3168 1.1859 0.851
ETTh2 720 3.4670 1.4730 3.1805 1.3668 3.0664 1.3084 0.884
ETTm1 24 0.3230 0.3690 0.3150 0.3886 0.3351 0.3875 0.975
ETTm1 48 0.4940 0.5030 0.4454 0.4620 0.4726 0.4702 0.902
ETTm1 96 0.6780 0.6140 0.4641 0.4823 0.4543 0.4831 0.670
ETTm1 288 1.0560 0.7860 0.6814 0.6312 0.6185 0.5991 0.586
ETTm1 672 1.1920 0.9260 1.1365 0.8572 1.1273 0.8412 0.946

State Of Art

PWC

PWC

PWC

PWC

PWC

PWC

PWC

PWC

PWC

PWC

Citation

@misc{klimek2021longterm,
      title={Long-term series forecasting with Query Selector -- efficient model of sparse attention}, 
      author={Jacek Klimek and Jakub Klimek and Witold Kraskiewicz and Mateusz Topolewski},
      year={2021},
      eprint={2107.08687},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

Contact

If you have any questions please contact us by email - [email protected]

Owner
MORAI
MORAI
Code for the paper titled "Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks" (NeurIPS 2021 Spotlight).

Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks This repository contains the code and pre-trained

Hassan Dbouk 7 Dec 05, 2022
FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control

FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control by Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hofmann FIGARO: Generat

Dimitri 83 Jan 07, 2023
Object detection and instance segmentation toolkit based on PaddlePaddle.

Object detection and instance segmentation toolkit based on PaddlePaddle.

9.3k Jan 02, 2023
Sequence-tagging using deep learning

Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface

Vineet Kumar 2 Dec 20, 2022
Tensorflow 2 Object Detection API kurulumu, GPU desteği, custom model hazırlama

Tensorflow 2 Object Detection API Bu tutorial, TensorFlow 2.x'in kararlı sürümü olan TensorFlow 2.3'ye yöneliktir. Bu, görüntülerde / videoda nesne a

46 Nov 20, 2022
Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary Differential Equations

ODE GAN (Prototype) in PyTorch Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary

Somshubra Majumdar 15 Feb 10, 2022
Catalyst.Detection

Accelerated DL R&D PyTorch framework for Deep Learning research and development. It was developed with a focus on reproducibility, fast experimentatio

Catalyst-Team 12 Oct 25, 2021
OpenMMLab 3D Human Parametric Model Toolbox and Benchmark

Introduction English | 简体中文 MMHuman3D is an open source PyTorch-based codebase for the use of 3D human parametric models in computer vision and comput

OpenMMLab 782 Jan 04, 2023
Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions

Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions Usage Clone the code to local. https://github.com/tanlab/MI

Computational Biology and Machine Learning lab @ TOBB ETU 3 Oct 18, 2022
This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (ICLR 2022)

Equivariant Subgraph Aggregation Networks (ESAN) This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (IC

Beatrice Bevilacqua 59 Dec 13, 2022
Graph WaveNet apdapted for brain connectivity analysis.

Graph WaveNet for brain network analysis This is the implementation of the Graph WaveNet model used in our manuscript: S. Wein , A. Schüller, A. M. To

4 Dec 17, 2022
WHENet: Real-time Fine-Grained Estimation for Wide Range Head Pose

WHENet: Real-time Fine-Grained Estimation for Wide Range Head Pose Yijun Zhou and James Gregson - BMVC2020 Abstract: We present an end-to-end head-pos

368 Dec 26, 2022
level1-image-classification-level1-recsys-09 created by GitHub Classroom

level1-image-classification-level1-recsys-09 ❗ 주제 설명 COVID-19 Pandemic 상황 속 마스크 착용 유무 판단 시스템 구축 마스크 착용 여부, 성별, 나이 총 세가지 기준에 따라 총 18개의 class로 구분하는 모델 ?

6 Mar 17, 2022
Recurrent Conditional Query Learning

Recurrent Conditional Query Learning (RCQL) This repository contains the Pytorch implementation of One Model Packs Thousands of Items with Recurrent C

Dongda 4 Nov 28, 2022
DeepAL: Deep Active Learning in Python

DeepAL: Deep Active Learning in Python Python implementations of the following active learning algorithms: Random Sampling Least Confidence [1] Margin

Kuan-Hao Huang 583 Jan 03, 2023
[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks

DiffMG This repository contains the code for our KDD 2021 Research Track paper: DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neura

AutoML Research 24 Nov 29, 2022
A full-fledged version of Pix2Seq

Stable-Pix2Seq A full-fledged version of Pix2Seq What it is. This is a full-fledged version of Pix2Seq. Compared with unofficial-pix2seq, stable-pix2s

peng gao 205 Dec 27, 2022
FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery (TGRS)

FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery by Ailong Ma, Junjue Wang*, Yanfei Zhon

Kingdrone 43 Jan 05, 2023
Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks.

Self Supervised Learning with Fastai Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks. Install pip install self-

Kerem Turgutlu 276 Dec 23, 2022
Supervised Classification from Text (P)

MSc-Thesis Module: Masters Research Thesis Language: Python Grade: 75 Title: An investigation of supervised classification of therapeutic process from

Matthew Laws 1 Nov 22, 2021