Recurrent Neural Networks for Time Series Forecasting: Current status and future directions von Hewamalage, Hansika, Bergmeir, Christoph, Bandara, Kasun

Volltext

Forecasting across time series databases using recurrent neural networks on groups of similar series: A clustering approach von Bandara, Kasun, Bergmeir, Christoph, Smyl, Slawek

Volltext

A note on the validity of cross-validation for evaluating autoregressive time series prediction von Bergmeir, Christoph, Hyndman, Rob J., Koo, Bonsoo

Volltext

On the use of cross-validation for time series predictor evaluation von Bergmeir, Christoph, Benítez, José M.

Volltext

Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation von Bergmeir, Christoph, Hyndman, Rob J., Benítez, José M.

Volltext

frbs : Fuzzy Rule-Based Systems for Classification and Regression in R von Riza, Lala Septem, Bergmeir, Christoph, Herrera, Francisco, Benítez, José Manuel

Volltext

Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study von Nanayakkara, Shane, Fogarty, Sam, Tremeer, Michael, Ross, Kelvin, Richards, Brent, Bergmeir, Christoph, Xu, Sheng, Stub, Dion, Smith, Karen, Tacey, Mark, Liew, Danny, Pilcher, David, Kaye, David M

Volltext

Pruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-Devices von Mohaimenuzzaman, Md, Bergmeir, Christoph, Meyer, Bernd

Volltext

A Generative Deep Learning Framework Across Time Series to Optimize the Energy Consumption of Air Conditioning Systems von Godahewa, Rakshitha, Deng, Chang, Prouzeau, Arnaud, Bergmeir, Christoph

Volltext

Implementing algorithms of rough set theory and fuzzy rough set theory in the R package “RoughSets” von Riza, Lala Septem, Janusz, Andrzej, Bergmeir, Christoph, Cornelis, Chris, Herrera, Francisco, Śle¸zak, Dominik, Benítez, José Manuel

Volltext

On the usefulness of cross-validation for directional forecast evaluation von Bergmeir, Christoph, Costantini, Mauro, Benítez, José M.

Volltext

Paying attention to cardiac surgical risk: An interpretable machine learning approach using an uncertainty-aware attentive neural network von Penny-Dimri, Jahan C, Bergmeir, Christoph, Reid, Christopher M, Williams-Spence, Jenni, Cochrane, Andrew D, Smith, Julian A

Volltext

Memetic Algorithms with Local Search Chains in R : The Rmalschains Package von Bergmeir, Christoph, Molina, Daniel, Benítez, José M.

Volltext

Designing a more efficient, effective and safe Medical Emergency Team (MET) service using data analysis von Bergmeir, Christoph, Bilgrami, Irma, Bain, Christopher, Webb, Geoffrey I, Orosz, Judit, Pilcher, David

Volltext

LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series With Multiple Seasonal Patterns von Bandara, Kasun, Bergmeir, Christoph, Hewamalage, Hansika

Volltext

Global models for time series forecasting: A Simulation study von Hewamalage, Hansika, Bergmeir, Christoph, Bandara, Kasun

Volltext

Forecast evaluation for data scientists: common pitfalls and best practices von Hewamalage, Hansika, Ackermann, Klaus, Bergmeir, Christoph

Volltext

Modelling risk-adjusted variation in length of stay among Australian and New Zealand ICUs von Straney, Lahn D, Udy, Andrew A, Burrell, Aidan, Bergmeir, Christoph, Huckson, Sue, Cooper, D James, Pilcher, David V

Volltext

Exploring the sources of uncertainty: Why does bagging for time series forecasting work? von Petropoulos, Fotios, Hyndman, Rob J., Bergmeir, Christoph

Volltext

Tree-based survival analysis improves mortality prediction in cardiac surgery von Penny-Dimri, Jahan C, Bergmeir, Christoph, Reid, Christopher M, Williams-Spence, Jenni, Perry, Luke A, Smith, Julian A

Volltext