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MultiRocket: Multiple pooling operators and transformations for fast and
  effective time series classification

MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification

31 January 2021
Chang Wei Tan
Angus Dempster
Christoph Bergmeir
Geoffrey I. Webb
    AI4TS
ArXivPDFHTML

Papers citing "MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification"

13 / 13 papers shown
Title
Time series classification with random convolution kernels: pooling operators and input representations matter
Time series classification with random convolution kernels: pooling operators and input representations matter
Mouhamadou Mansour Lo
Gildas Morvan
Mathieu Rossi
Fabrice Morganti
David Mercier
AI4TS
26
0
0
02 Sep 2024
RandomNet: Clustering Time Series Using Untrained Deep Neural Networks
RandomNet: Clustering Time Series Using Untrained Deep Neural Networks
Xiaosheng Li
Wenjie Xi
Jessica Lin
AI4TS
23
2
0
15 Aug 2024
Nonlinear time-series embedding by monotone variational inequality
Nonlinear time-series embedding by monotone variational inequality
Jonathan Y. Zhou
Yao Xie
AI4TS
36
0
0
11 Jun 2024
TSCMamba: Mamba Meets Multi-View Learning for Time Series Classification
TSCMamba: Mamba Meets Multi-View Learning for Time Series Classification
Md Atik Ahamed
Qiang Cheng
Mamba
68
1
0
06 Jun 2024
Finding Foundation Models for Time Series Classification with a PreText
  Task
Finding Foundation Models for Time Series Classification with a PreText Task
Ali Ismail-Fawaz
Maxime Devanne
Stefano Berretti
Jonathan Weber
Germain Forestier
34
5
0
24 Nov 2023
Detach-ROCKET: Sequential feature selection for time series
  classification with random convolutional kernels
Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernels
Gonzalo Uribarri
Federico Barone
A. Ansuini
Erik Fransén
AI4TS
50
6
0
25 Sep 2023
Automatic Feature Engineering for Time Series Classification: Evaluation
  and Discussion
Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion
Aurélien Renault
A. Bondu
V. Lemaire
D. Gay
AI4TS
33
1
0
02 Aug 2023
QUANT: A Minimalist Interval Method for Time Series Classification
QUANT: A Minimalist Interval Method for Time Series Classification
Angus Dempster
Daniel F. Schmidt
Geoffrey I. Webb
AI4TS
19
9
0
02 Aug 2023
Unsupervised Feature Based Algorithms for Time Series Extrinsic
  Regression
Unsupervised Feature Based Algorithms for Time Series Extrinsic Regression
David Guijo Rubio
Matthew Middlehurst
Guilherme G. Arcencio
Diego Furtado Silva
A. Bagnall
AI4TS
38
9
0
02 May 2023
TimeMAE: Self-Supervised Representations of Time Series with Decoupled
  Masked Autoencoders
TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders
Mingyue Cheng
Qi Liu
Zhiding Liu
Haotong Zhang
Rujiao Zhang
Enhong Chen
AI4TS
42
42
0
01 Mar 2023
ConfLab: A Data Collection Concept, Dataset, and Benchmark for Machine
  Analysis of Free-Standing Social Interactions in the Wild
ConfLab: A Data Collection Concept, Dataset, and Benchmark for Machine Analysis of Free-Standing Social Interactions in the Wild
Chirag Raman
Jose Vargas-Quiros
Stephanie Tan
Ashraful Islam
Ekin Gedik
Hayley Hung
19
8
0
10 May 2022
Domain Adaptation for Time-Series Classification to Mitigate Covariate
  Shift
Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift
Felix Ott
David Rügamer
Lucas Heublein
Bernd Bischl
Christopher Mutschler
OOD
TTA
AI4TS
33
31
0
07 Apr 2022
InceptionTime: Finding AlexNet for Time Series Classification
InceptionTime: Finding AlexNet for Time Series Classification
Hassan Ismail Fawaz
Benjamin Lucas
Germain Forestier
Charlotte Pelletier
Daniel F. Schmidt
J. Weber
Geoffrey I. Webb
L. Idoumghar
Pierre-Alain Muller
Franccois Petitjean
AI4TS
104
1,073
0
11 Sep 2019
1