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ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels

Data mining and knowledge discovery, 2020-09, Vol.34 (5), p.1454-1495

2020

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InceptionTime: Finding AlexNet for time series classification

Data mining and knowledge discovery, 2020-11, Vol.34 (6), p.1936-1962

2020

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Proximity Forest: an effective and scalable distance-based classifier for time series

Data mining and knowledge discovery, 2019-05, Vol.33 (3), p.607-635

2019

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SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting

Machine learning, 2023-07, Vol.112 (7), p.2555-2591

2023

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Positive-unlabelled learning of glycosylation sites in the human proteome

BMC bioinformatics, 2019-03, Vol.20 (1), p.112-112, Article 112

2019

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SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models

BMC bioinformatics, 2019-11, Vol.20 (1), p.602-12, Article 602

2019

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Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification

Machine learning, 2012-02, Vol.86 (2), p.233-272

2012

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

Data mining and knowledge discovery, 2022-09, Vol.36 (5), p.1623-1646

2022

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Layered critical values: a powerful direct-adjustment approach to discovering significant patterns

Machine learning, 2008-06, Vol.71 (2-3), p.307-323

Webb, Geoffrey I.

2008

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TS-CHIEF: a scalable and accurate forest algorithm for time series classification

Data mining and knowledge discovery, 2020-05, Vol.34 (3), p.742-775

2020

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Characterizing concept drift

Data mining and knowledge discovery, 2016-07, Vol.30 (4), p.964-994

2016

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A tutorial on statistically sound pattern discovery

Data mining and knowledge discovery, 2019-03, Vol.33 (2), p.325-377

2019

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Hydra: competing convolutional kernels for fast and accurate time series classification

Data mining and knowledge discovery, 2023-09, Vol.37 (5), p.1779-1805

2023

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Discovering significant patterns

Machine learning, 2007-07, Vol.68 (1), p.1-33

WEBB, Geoffrey I

2007

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Early abandoning and pruning for elastic distances including dynamic time warping

Data mining and knowledge discovery, 2021-11, Vol.35 (6), p.2577-2601

2021

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A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping

Machine learning, 2023-06, Vol.112 (6), p.1941-1973

2023

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Survey of distance measures for quantifying concept drift and shift in numeric data

Knowledge and information systems, 2019-08, Vol.60 (2), p.591-615

2019

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Time series extrinsic regression: Predicting numeric values from time series data

Data mining and knowledge discovery, 2021, Vol.35 (3), p.1032-1060

2021

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Analyzing concept drift and shift from sample data

Data mining and knowledge discovery, 2018-09, Vol.32 (5), p.1179-1199

2018

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Discretization for naive-Bayes learning: managing discretization bias and variance

Machine learning, 2009, Vol.74 (1), p.39-74

2009

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Improving position encoding of transformers for multivariate time series classification

Data mining and knowledge discovery, 2024, Vol.38 (1), p.22-48

2024

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Feature-subspace aggregating: ensembles for stable and unstable learners

Machine learning, 2011-03, Vol.82 (3), p.375-397

2011

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Series2vec: similarity-based self-supervised representation learning for time series classification

Data mining and knowledge discovery, 2024-07, Vol.38 (4), p.2520-2544

2024

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quant: a minimalist interval method for time series classification

Data mining and knowledge discovery, 2024-07, Vol.38 (4), p.2377-2402

2024

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Parameterizing the cost function of dynamic time warping with application to time series classification

Data mining and knowledge discovery, 2023-09, Vol.37 (5), p.2024-2045

2023

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ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels

InceptionTime: Finding AlexNet for time series classification

Proximity Forest: an effective and scalable distance-based classifier for time series

SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting

Positive-unlabelled learning of glycosylation sites in the human proteome

SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models

Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification

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

Layered critical values: a powerful direct-adjustment approach to discovering significant patterns

TS-CHIEF: a scalable and accurate forest algorithm for time series classification

Characterizing concept drift

A tutorial on statistically sound pattern discovery

Hydra: competing convolutional kernels for fast and accurate time series classification

Discovering significant patterns

Early abandoning and pruning for elastic distances including dynamic time warping

A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping

Survey of distance measures for quantifying concept drift and shift in numeric data

Time series extrinsic regression: Predicting numeric values from time series data

Analyzing concept drift and shift from sample data

Discretization for naive-Bayes learning: managing discretization bias and variance

Improving position encoding of transformers for multivariate time series classification

Feature-subspace aggregating: ensembles for stable and unstable learners

Series2vec: similarity-based self-supervised representation learning for time series classification

quant: a minimalist interval method for time series classification

Parameterizing the cost function of dynamic time warping with application to time series classification

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