Christoph Bergmeir
Orcid: 0000-0002-3665-9021
According to our database1,
Christoph Bergmeir
authored at least 71 papers
between 2008 and 2024.
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Bibliography
2024
Probabilistic Causal Effect Estimation With Global Neural Network Forecasting Models.
IEEE Trans. Neural Networks Learn. Syst., April, 2024
2023
Mach. Learn., July, 2023
Data Min. Knowl. Discov., March, 2023
Environmental Sound Classification on the Edge: A Pipeline for Deep Acoustic Networks on Extremely Resource-Constrained Devices.
Pattern Recognit., 2023
The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyond.
CoRR, 2023
Scalable Probabilistic Forecasting in Retail with Gradient Boosted Trees: A Practitioner's Approach.
CoRR, 2023
2022
IEEE Trans. Software Eng., 2022
Pattern Recognit., 2022
MultiRocket: multiple pooling operators and transformations for fast and effective time series classification.
Data Min. Knowl. Discov., 2022
Comparison and Evaluation of Methods for a Predict+Optimize Problem in Renewable Energy.
CoRR, 2022
CoRR, 2022
Causal Effect Estimation with Global Probabilistic Forecasting: A Case Study of the Impact of Covid-19 Lockdowns on Energy Demand.
CoRR, 2022
Pruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-Devices.
IEEE Access, 2022
A Generative Deep Learning Framework Across Time Series to Optimize the Energy Consumption of Air Conditioning Systems.
IEEE Access, 2022
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022
RNN-BOF: A Multivariate Global Recurrent Neural Network for Binary Outcome Forecasting of Inpatient Aggression.
Proceedings of the International Joint Conference on Neural Networks, 2022
LIMREF: Local Interpretable Model Agnostic Rule-Based Explanations for Forecasting, with an Application to Electricity Smart Meter Data.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series With Multiple Seasonal Patterns.
IEEE Trans. Neural Networks Learn. Syst., 2021
Improving the accuracy of global forecasting models using time series data augmentation.
Pattern Recognit., 2021
LoMEF: A Framework to Produce Local Explanations for Global Model Time Series Forecasts.
CoRR, 2021
Environmental Sound Classification on the Edge: Deep Acoustic Networks for Extremely Resource-Constrained Devices.
CoRR, 2021
CoRR, 2021
MultiRocket: Effective summary statistics for convolutional outputs in time series classification.
CoRR, 2021
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
Proceedings of the Neural Information Processing - 28th International Conference, 2021
2020
Inf. Sci., 2020
Forecasting across time series databases using recurrent neural networks on groups of similar series: A clustering approach.
Expert Syst. Appl., 2020
CoRR, 2020
Seasonal Averaged One-Dependence Estimators: A Novel Algorithm to Address Seasonal Concept Drift in High-Dimensional Stream Classification.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Towards Accurate Predictions and Causal 'What-if' Analyses for Planning and Policy-making: A Case Study in Emergency Medical Services Demand.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Proceedings of the AI 2020: Advances in Artificial Intelligence, 2020
2019
Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions.
CoRR, 2019
Sales Demand Forecast in E-commerce Using a Long Short-Term Memory Neural Network Methodology.
Proceedings of the Neural Information Processing - 26th International Conference, 2019
2018
IEEE Trans. Cloud Comput., 2018
Self-labeling techniques for semi-supervised time series classification: an empirical study.
Knowl. Inf. Syst., 2018
J. Comput. Civ. Eng., 2018
Exploring the sources of uncertainty: Why does bagging for time series forecasting work?
Eur. J. Oper. Res., 2018
A note on the validity of cross-validation for evaluating autoregressive time series prediction.
Comput. Stat. Data Anal., 2018
2017
Forecasting Across Time Series Databases using Long Short-Term Memory Networks on Groups of Similar Series.
CoRR, 2017
2016
On the stopping criteria for k-Nearest Neighbor in positive unlabeled time series classification problems.
Inf. Sci., 2016
2014
Implementing algorithms of rough set theory and fuzzy rough set theory in the R package "RoughSets".
Inf. Sci., 2014
Comput. Stat. Data Anal., 2014
Proceedings of the IEEE International Conference on Fuzzy Systems, 2014
2013
A Study on the Use of Machine Learning Methods for Incidence Prediction in High-Speed Train Tracks.
Proceedings of the Recent Trends in Applied Artificial Intelligence, 2013
2012
Time Series Modeling and Forecasting Using Memetic Algorithms for Regime-Switching Models.
IEEE Trans. Neural Networks Learn. Syst., 2012
Segmentation of cervical cell nuclei in high-resolution microscopic images: A new algorithm and a web-based software framework.
Comput. Methods Programs Biomed., 2012
Optimization of Neuro-Coefficient Smooth Transition Autoregressive Models Using Differential Evolution.
Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012
2011
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011
2010
Segmentation of cervical cell images using mean-shift filtering and morphological operators.
Proceedings of the Medical Imaging 2010: Image Processing, 2010
2009
Int. J. Comput. Assist. Radiol. Surg., 2009
Klassifikation von Standardebenen in der 2D-Echokardiographie mittels 2D-3D-Bildregistrierung.
Proceedings of the Bildverarbeitung für die Medizin 2009: Algorithmen - Systeme, 2009
2008
Proceedings of the Bildverarbeitung für die Medizin 2008, 2008