Research group on MACHINE LEARNING

Faculty of Mathematics and Computer Science, Babes-Bolyai University, Romania

1. Czibula, G., Codre C., Teletin, M., AnomalP: An approach for detecting anomalous protein conformations using deep autoencoders, Expert systems with Applications, Volume 166, 15 March 2021, 114070 (WoS, Q1)
2. Czibula, G., Andrei, M., Mihuleț, E., NowDeepN: An ensemble of deep learning models for weather nowcasting based on radar products' values prediction, Applied Sciences, 2021, 11(1), 125; https://doi.org/10.3390/app11010125. (WoS, Q2)
3. Gabriela Czibula, Alexandra Albu, Maria Iuliana Bocicor, Camelia Chira, AutoPPI: An ensemble of deep autoencoders for protein-protein interaction prediction, Entropy, Special issue on Computational Methods and Algorithms for Bioinformatics, 23(6), 643, 2021, https://www.mdpi.com/1099-4300/23/6/643 WoS, Q2
4. Czibula G., Mihai, A., Albu, A.-I., Czibula, I.G., Burcea, S. Mezghani, A., AutoNowP: An approach using deep autoencoders for precipitation nowcasting based on weather radar reflectivity prediction, Mathematics, 9(14):1653. https://doi.org/10.3390/math9141653, Special Issue on Computational Optimizations for Machine Learning, 2021 WoS, Q1
5. Zsuzsanna Oneț-Marian , Gabriela Czibula, Mariana-Ioana Maier, Using self-organizing maps for comparing students' academic performance in online and traditional learning environments, Studies in Informatics and Control, vol 31(4), 2021 in press WoS, Q3
6. Mariana-Ioana Maier, Gabriela Czibula, Zsuzsanna Oneț-Marian, Towards Using Deep Autoencoders for Comparing Traditional and Synchronous Online Learning in Assessing Students' Academic Performance, Mathematics, Engineering Mathematics - special issue on Didactics and Technology in Mathematical Education, 2021, 9(22), 2870 WoS, Q1
7. Bratu A., Czibula G., DAuGAN: An approach for augmenting time series imbalanced datasets via latent space sampling using adversarial techniques, Scientific Programming, Volume 2021, Article ID 7877590 | https://doi.org/10.1155/2021/7877590 WoS, Q4
8. Sergiu Cosmin Nistor, Mircea Moca, Darie Moldovan, Delia Beatrice Oprean and Răzvan Liviu Nistor, Building a Twitter Sentiment Analysis System with Recurrent Neural Networks, Sensors (2021), 21, 7, 2266 WoS, Q1
9. Sergiu Cosmin Nistor, Mircea Moca and Răzvan Liviu Nistor, Discovering Novel MemoryCell Designs for Sentiment Analysis on Tweets. Genetic Programming and Evolvable Machines (2021): 22, 2, 147-187, Springer WoS, Q2
10. Zsuzsanna Oneț-Marian, Gabriela Czibula, Mariana Maier. Using self-organizingmaps for comparing students’ academic performance in online and traditional learning environment(2021). Studies in Informatics and Control, 30(4), pp. 1–11 WoS, Q3
11. Mihaiela LUPEA, Anamaria BRICIU, Elena BOSTENARU, Emotion-based Hierarchical Clustering of Romanian Poetry, Studies in Informatics and Control, ISSN 1220-1766, vol. 30(1), pp. 109-118, 2021. WoS, Q3
12. Ciorîță, A.; Tripon, S.C.; Mircea, I.G.; Podar, D.; Barbu-Tudoran, L.; Mircea, C.; Pârvu, M. The Morphological and Anatomical Traits of the Leaf in Representative Vinca Species Observed on Indoor- and Outdoor-Grown Plants. Plants 2021, 10, 622. WoS, Q1
13. Vlad-Ioan Tomescu, Gabriela Czibula, Ștefan Nițică, A study on using deep autoencoders for imbalanced binary classification, 25thInternational Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2021), Procedia Computer Science, Volume 192, 2021, Pages 119-128
14. Anamaria Briciu, Gabriela Czibula, Mihaiela Lupea, AutoAt: A deep autoencoder-based classification model for supervised authorship attribution, 25thInternational Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2021), Procedia Computer Science, Volume 192, 2021, Pages 119-128
15. Vlad-Sebastian Ionescu, Gabriela Czibula, Eugen Mihuleț, DeePSat: A deep learning model for prediction of satellite images for nowcasting purposes, 25th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2021), Procedia Computer Science Volume 192, 2021, Pages 622-631
16. George Ciubotariu, Vlad-Ioan Tomescu, Gabriela Czibula, Enhancing the performance of image classification through features automatically learned from depth-maps, 13th International Conference on Computer Vision Systems, September 22-24, 2021, LNCS 12899, pp. 68-81
17. Maria-Mădălina Mircea, Rareș Boian and Gabriela Czibula, A machine learning approach for data protection in virtual reality therapy applications, 2021 IEEE 17th International Conference on Intelligent Computer Communication and Processing, 2021, accepted for publication
18. Sergiu Cosmin Nistor. An Actor-Critic Approach to Neural Network Architecture Search for Facial Expressions Recognition. 2021 17th IEEE International Conference on IntelligentComputer Communication and Processing (ICCP), IEEE, 2021, accepted for publication
19. Alexandra-Ioana Albu. Towards learning transferable embeddings for protein conformations using Variational Autoencoders. 25th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2021), Procedia Com-puter Science, Volume 192, 2021, Pages 10–19.
20. Diana-Lucia Miholca New Conceptual Cohesion Metrics: Assessment for Software Defect Prediction, 23rd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2021, pp. 163-170, DOI: 10.1109/SYNASC54541.2021.00036 (WoS Proceedings)