Browse by UCL people
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Number of items: 12.
Article
Ghomeshi, Hossein;
Gaber, Mohamed Medhat;
Kovalchuk, Yevgeniya;
(2019)
EACD: evolutionary adaptation to concept drifts in data streams.
Data Mining and Knowledge Discovery
, 33
pp. 663-694.
10.1007/s10618-019-00614-6.
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Ghomeshi, Hossein;
Gaber, Mohamed Medhat;
Kovalchuk, Yevgeniya;
(2019)
RED-GENE: An Evolutionary Game Theoretic Approach to Adaptive Data Stream Classification.
IEEE Access
, 7
pp. 173944-173954.
10.1109/access.2019.2954993.
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Hanga, Khadijah M;
Kovalchuk, Yevgeniya;
(2019)
Machine learning and multi-agent systems in oil and gas industry applications: A survey.
Computer Science Review
, 34
, Article 100191. 10.1016/j.cosrev.2019.08.002.
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Hanga, Khadijah Muzzammil;
Kovalchuk, Yevgeniya;
Gaber, Mohamed Medhat;
(2022)
A Graph-Based Approach to Interpreting Recurrent Neural Networks in Process Mining.
IEEE Access
, 8
pp. 172923-172938.
10.1109/ACCESS.2020.3025999.
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Hanga, Khadijah Muzzammil;
Kovalchuk, Yevgeniya;
Gaber, Mohamed Medhat;
(2022)
PGraphD*: Methods for Drift Detection and Localisation Using Deep Learning Modelling of Business Processes.
Entropy
, 24
(7)
, Article 910. 10.3390/e24070910.
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Kovalchuk, Yevgeniya;
Budini, Elizabeta;
Cook, Robert M;
Walsh, Andrew;
(2022)
Investigating the Relationship between Facial Mimicry and Empathy.
Behavioural Sciences
, 12
(8)
, Article 250. 10.3390/bs12080250.
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Sambo, Aliyu Sani;
Azad, R Muhammad Atif;
Kovalchuk, Yevgeniya;
Indramohan, Vivek Padmanaabhan;
Shah, Hanifa;
(2021)
Evolving simple and accurate symbolic regression models via asynchronous parallel computing.
Applied Soft Computing
, 104
, Article 107198. 10.1016/j.asoc.2021.107198.
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Spuler, Fiona R;
Kretschmer, Marlene;
Balmaseda, Magdalena Alonso;
Kovalchuk, Yevgeniya;
Shepherd, Theodore G;
(2025)
Learning predictable and informative dynamical drivers of extreme precipitation using variational autoencoders.
Weather and Climate Dynamics
, 6
(3)
pp. 995-1014.
10.5194/wcd-6-995-2025.
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Spuler, Fiona R;
Kretschmer, Marlene;
Kovalchuk, Yevgeniya;
Balmaseda, Magdalena Alonso;
Shepherd, Theodore G;
(2024)
Identifying probabilistic weather regimes targeted to a local-scale impact variable.
Environmental Data Science
, 3
, Article e25. 10.1017/eds.2024.29.
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Proceedings paper
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Sambo, Aliyu Sani;
Azad, R Muhammad Atif;
Kovalchuk, Yevgeniya;
Indramohan, Vivek Padmanaabhan;
Shah, Hanifa;
(2020)
Time Control or Size Control? Reducing Complexity and Improving Accuracy of Genetic Programming Models.
In: Hu, T and Lourenco, N and Medvet, E and Divina, F, (eds.)
Genetic Programming.
(pp. pp. 195-210).
Springer: Cham, Switzerland.
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Sambo, Aliyu Sani;
Azad, R Muhammad Atif;
Kovalchuk, Yevgeniya;
Padmanaabhan, Vivek;
Shah, Hanifa;
(2021)
Improving the generalisation of genetic programming models with evaluation time and asynchronous parallel computing.
In:
Proceedings of the Genetic and Evolutionary Computation Conference Companion.
(pp. pp. 265-266).
ACM (Association for Computing Machinery)
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Spuler, FR;
Kretschmer, M;
Kovalchuk, Y;
Balmaseda, MA;
Shepherd, TG;
(2023)
RMM-VAE: a machine learning method for identifying probabilistic weather regimes targeted to a local-scale impact variable.
In:
Tackling Climate Change with Machine Learning: workshop at NeurIPS 2023.
Climate Change AI
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