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Recurrent Neural Networks for Time Series Forecasting: Current status and future directions

International journal of forecasting, 2021-01, Vol.37 (1), p.388-427

2021

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Forecasting across time series databases using recurrent neural networks on groups of similar series: A clustering approach

Expert systems with applications, 2020-02, Vol.140, p.112896, Article 112896

2020

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A note on the validity of cross-validation for evaluating autoregressive time series prediction

Computational statistics & data analysis, 2018-04, Vol.120, p.70-83

2018

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On the use of cross-validation for time series predictor evaluation

Information sciences, 2012-05, Vol.191, p.192-213

2012

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frbs : Fuzzy Rule-Based Systems for Classification and Regression in R

Journal of statistical software, 2015-05, Vol.65 (6), p.1-30

2015

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Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation

International journal of forecasting, 2016-04, Vol.32 (2), p.303-312

2016

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Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study

PLoS medicine, 2018-11, Vol.15 (11), p.e1002709-e1002709

2018

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Pruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-Devices

IEEE access, 2022, Vol.10, p.6696-6707

2022

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Implementing algorithms of rough set theory and fuzzy rough set theory in the R package “RoughSets”

Information sciences, 2014-12, Vol.287, p.68-89

2014

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A Generative Deep Learning Framework Across Time Series to Optimize the Energy Consumption of Air Conditioning Systems

IEEE access, 2022, Vol.10, p.6842-6855

2022

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Paying attention to cardiac surgical risk: An interpretable machine learning approach using an uncertainty-aware attentive neural network

PloS one, 2023-08, Vol.18 (8), p.e0289930-e0289930

2023

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On the usefulness of cross-validation for directional forecast evaluation

Computational statistics & data analysis, 2014-08, Vol.76, p.132-143

2014

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Memetic Algorithms with Local Search Chains in R : The Rmalschains Package

Journal of statistical software, 2016-12, Vol.75 (4), p.1-33

2016

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Designing a more efficient, effective and safe Medical Emergency Team (MET) service using data analysis

PloS one, 2017-12, Vol.12 (12), p.e0188688-e0188688

2017

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LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series With Multiple Seasonal Patterns

IEEE transaction on neural networks and learning systems, 2021-04, Vol.32 (4), p.1586-1599

2021

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Modelling risk-adjusted variation in length of stay among Australian and New Zealand ICUs

PloS one, 2017-05, Vol.12 (5), p.e0176570-e0176570

2017

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Global models for time series forecasting: A Simulation study

Pattern recognition, 2022-04, Vol.124, p.108441, Article 108441

2022

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Exploring the sources of uncertainty: Why does bagging for time series forecasting work?

European journal of operational research, 2018-07, Vol.268 (2), p.545-554

2018

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Tree-based survival analysis improves mortality prediction in cardiac surgery

Frontiers in cardiovascular medicine, 2023-07, Vol.10, p.1211600-1211600

2023

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LoRMIkA: Local rule-based model interpretability with k-optimal associations

Information sciences, 2020-11, Vol.540, p.221-241

2020

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Forecast evaluation for data scientists: common pitfalls and best practices

Data mining and knowledge discovery, 2023-03, Vol.37 (2), p.788-832

2023

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Adaptive dependency learning graph neural networks

Information sciences, 2023-05, Vol.625, p.700-714

2023

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Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions

International journal of forecasting, 2024-04, Vol.40 (2), p.597-615

2024

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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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Closing the Gap in Surveillance and Audit of Invasive Mold Diseases for Antifungal Stewardship Using Machine Learning

Journal of clinical medicine, 2019-09, Vol.8 (9), p.1390

2019

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Recurrent Neural Networks for Time Series Forecasting: Current status and future directions

Forecasting across time series databases using recurrent neural networks on groups of similar series: A clustering approach

A note on the validity of cross-validation for evaluating autoregressive time series prediction

On the use of cross-validation for time series predictor evaluation

frbs : Fuzzy Rule-Based Systems for Classification and Regression in R

Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation

Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study

Pruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-Devices

Implementing algorithms of rough set theory and fuzzy rough set theory in the R package “RoughSets”

A Generative Deep Learning Framework Across Time Series to Optimize the Energy Consumption of Air Conditioning Systems

Paying attention to cardiac surgical risk: An interpretable machine learning approach using an uncertainty-aware attentive neural network

On the usefulness of cross-validation for directional forecast evaluation

Memetic Algorithms with Local Search Chains in R : The Rmalschains Package

Designing a more efficient, effective and safe Medical Emergency Team (MET) service using data analysis

LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series With Multiple Seasonal Patterns

Modelling risk-adjusted variation in length of stay among Australian and New Zealand ICUs

Global models for time series forecasting: A Simulation study

Exploring the sources of uncertainty: Why does bagging for time series forecasting work?

Tree-based survival analysis improves mortality prediction in cardiac surgery

LoRMIkA: Local rule-based model interpretability with k-optimal associations

Forecast evaluation for data scientists: common pitfalls and best practices

Adaptive dependency learning graph neural networks

Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions

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

Closing the Gap in Surveillance and Audit of Invasive Mold Diseases for Antifungal Stewardship Using Machine Learning

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