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Alexandra Brintrup
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Digital twins: State of the art theory and practice, challenges, and open research questions
A Sharma, E Kosasih, J Zhang, A Brintrup, A Calinescu
Journal of Industrial Information Integration 30, 100383, 2022
3862022
High-quality prediction intervals for deep learning: A distribution-free, ensembled approach
T Pearce, A Brintrup, M Zaki, A Neely
International conference on machine learning, 4075-4084, 2018
3462018
Uncertainty in neural networks: Approximately bayesian ensembling
T Pearce, F Leibfried, A Brintrup
International conference on artificial intelligence and statistics, 234-244, 2020
325*2020
Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing
A Brintrup, J Pak, D Ratiney, T Pearce, P Wichmann, P Woodall, ...
International Journal of Production Research 58 (11), 3330-3341, 2020
2032020
RFID opportunity analysis for leaner manufacturing
A Brintrup, D Ranasinghe, D McFarlane
International Journal of Production Research 48 (9), 2745-2764, 2010
1362010
Ergonomic chair design by fusing qualitative and quantitative criteria using interactive genetic algorithms
AM Brintrup, J Ramsden, H Takagi, A Tiwari
IEEE Transactions on Evolutionary Computation 12 (3), 343-354, 2008
1362008
A machine learning approach for predicting hidden links in supply chain with graph neural networks
EE Kosasih, A Brintrup
International Journal of Production Research 60 (17), 5380-5393, 2022
1352022
An interactive genetic algorithm-based framework for handling qualitative criteria in design optimization
AM Brintrup, J Ramsden, A Tiwari
Computers in Industry 58 (3), 279-291, 2007
1242007
A review of Pareto pruning methods for multi-objective optimization
S Petchrompo, DW Coit, A Brintrup, A Wannakrairot, AK Parlikad
Computers & Industrial Engineering 167, 108022, 2022
1112022
Supply networks as complex systems: a network-science-based characterization
A Brintrup, Y Wang, A Tiwari
IEEE Systems Journal 11 (4), 2170-2181, 2015
1112015
Extracting supply chain maps from news articles using deep neural networks
P Wichmann, A Brintrup, S Baker, P Woodall, D McFarlane
International Journal of Production Research 58 (17), 5320-5336, 2020
1102020
Understanding softmax confidence and uncertainty
T Pearce, A Brintrup, J Zhu
arXiv preprint arXiv:2106.04972, 2021
1002021
The structure of the Toyota supply network: an empirical analysis
T Kito, A Brintrup, S New, F Reed-Tsochas
Saïd Business School WP 3, 2014
832014
The moderating impact of supply network topology on the effectiveness of risk management
A Ledwoch, H Yasarcan, A Brintrup
International Journal of Production Economics 197, 13-26, 2018
782018
Behaviour adaptation in the multi-agent, multi-objective and multi-role supply chain
A Brintrup
Computers in Industry 61 (7), 636-645, 2010
712010
Topological robustness of the global automotive industry
A Brintrup, A Ledwoch, J Barros
Logistics Research 9, 1-17, 2016
692016
A generative neural network model for the quality prediction of work in progress products
G Wang, A Ledwoch, RM Hasani, R Grosu, A Brintrup
Applied Soft Computing 85, 105683, 2019
632019
Expressive priors in Bayesian neural networks: Kernel combinations and periodic functions
T Pearce, R Tsuchida, M Zaki, A Brintrup, A Neely
Uncertainty in artificial intelligence, 134-144, 2020
622020
Towards knowledge graph reasoning for supply chain risk management using graph neural networks
EE Kosasih, F Margaroli, S Gelli, A Aziz, N Wildgoose, A Brintrup
International Journal of Production Research 62 (15), 5596-5612, 2024
612024
Fast machine unlearning without retraining through selective synaptic dampening
J Foster, S Schoepf, A Brintrup
Proceedings of the AAAI Conference on Artificial Intelligence 38 (11), 12043 …, 2024
602024
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Articles 1–20