Publications

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Magris, M., Shabani, M. & Iosifidis, A. (2023). Bayesian bilinear neural network for predicting the mid-price dynamics in limit-order book markets. Journal of Forecasting, 42(6), 1407-1428. https://doi.org/10.1002/for.2955

Magris, M. & Iosifidis, A. (2023). Bayesian learning for neural networks: an algorithmic survey. Artificial Intelligence Review, 56(10), 11773-11823. https://doi.org/10.1007/s10462-023-10443-1

Rafiei Foroushani, M. & Iosifidis, A. (2023). Class-Specific Variational Auto-Encoder for Content-Based Image Retrieval. I 2023 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN54540.2023.10191068

Rafiei Foroushani, M., Raitoharju, J. & Iosifidis, A. (2023). Computer Vision on X-Ray Data in Industrial Production and Security Applications: A Comprehensive Survey. IEEE Access, 11, 2445 - 2477. https://doi.org/10.1109/ACCESS.2023.3234187

Legaard, C. M., Schranz, T., Schweiger, G., Drgona, J., Falay, B., Gomes, C., Iosifidis, A., Abkar, M. & Larsen, P. G. (2023). Constructing Neural Network Based Models for Simulating Dynamical Systems. ACM Computing Surveys, 55(11), 1-34. Artikel 236. https://doi.org/10.1145/3567591

Hedegaard, L. & Iosifidis, A. (2023). Continual Inference: A Library for Efficient Online Inference with Deep Neural Networks in PyTorch. I L. Karlinsky, T. Michaeli & K. Nishino (red.), Computer Vision – ECCV 2022 Workshops, Proceedings (s. 21-34). Springer. https://doi.org/10.1007/978-3-031-25082-8_2

Hedegaard Morsing, L., Heidari, N. & Iosifidis, A. (2023). Continual Spatio-Temporal Graph Convolutional Networks. Pattern Recognition, 140(C), Artikel 109528. https://doi.org/10.1016/j.patcog.2023.109528

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2023). Crowd Counting on Heavily Compressed Images with Curriculum Pre-Training. I 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (s. 559-564). IEEE. https://doi.org/10.1109/SSCI52147.2023.10371805

Amarloo, A., Cinnella, P., Iosifidis, A., Forooghi, P. & Abkar, M. (2023). Data-driven Reynolds stress models based on the frozen treatment of Reynolds stress tensor and Reynolds force vector. Physics of Fluids, 35(7), Artikel 075154. https://doi.org/10.1063/5.0160977

Bakhtiarnia, A., Milošević, N., Zhang, Q., Bajović, D. & Iosifidis, A. (2023). Dynamic Split Computing for Efficient Deep Edge Intelligence. I ICASSP 2023: 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) IEEE. https://doi.org/10.1109/ICASSP49357.2023.10096914

Jensen, R. I. T. & Iosifidis, A. (2023). Fighting Money Laundering With Statistics and Machine Learning. IEEE Access, 11, 8889-8903. https://doi.org/10.1109/ACCESS.2023.3239549

Sohrab, F., Iosifidis, A., Gabbouj, M. & Raitoharju, J. (2023). Graph-embedded subspace support vector data description. Pattern Recognition, 133, Artikel 108999. https://doi.org/10.1016/j.patcog.2022.108999

Wewer, C. R. & Iosifidis, A. (2023). Improving Online non-destructive Moisture Content Estimation using Data Augmentation by Feature Space Interpolation with Variational Autoencoders. I 2023 IEEE 21st International Conference on Industrial Informatics (INDIN) IEEE. https://doi.org/10.1109/INDIN51400.2023.10218063

Amarloo, A., Cinnella, P., Iosifidis, A., Forooghi, P. & Abkar, M. (2023). Investigation of Data-driven algebraic Reynolds stress models for turbulent secondary flows. I The 14th International ERCOFTAC Symposium on Engineering Turbulence Modelling and Measurements Proceedings https://www.ercoftac.org/etmm/program/conference-program/

Oleksiienko, I. & Iosifidis, A. (2023). Layer Ensembles. I D. Comminiello & M. Scarpiniti (red.), 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP) IEEE. https://doi.org/10.1109/MLSP55844.2023.10286005

Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2023). Learning Distinct Features Helps, Provably. I D. Koutra, C. Plant, M. Gomez Rodriguez, E. Baralis & F. Bonchi (red.), Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part II (s. 206-222). Springer. https://doi.org/10.1007/978-3-031-43415-0_13

Zehtabiyan-Rezaie, N., Iosifidis, A. & Abkar, M. (2023). Physics-Guided Machine Learning for Wind-Farm Power Prediction: Toward Interpretability and Generalizability. PRX Energy, 2(1), Artikel 013009. https://doi.org/10.1103/PRXEnergy.2.013009

Shabani, M., Magris, M., Tzagkarakis, G., Kanniainen, J. & Iosifidis, A. (2023). Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots. Neural Computing and Applications, 35(25), 18519–18531. https://doi.org/10.1007/s00521-023-08674-y

Baltakys, K., Baltakienė, M., Heidari, N., Iosifidis, A. & Kanniainen, J. (2023). Predicting the trading behavior of socially connected investors: Graph neural network approach with implications to market surveillance. Expert Systems with Applications, 228, Artikel 120285. https://doi.org/10.1016/j.eswa.2023.120285

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2023). PromptMix: Text-to-image diffusion models enhance the performance of lightweight networks. I 2023 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN54540.2023.10191962

Jensen, R. I. T. & Iosifidis, A. (2023). Qualifying and raising anti-money laundering alarms with deep learning. Expert Systems with Applications, 214, Artikel 119037. https://doi.org/10.1016/j.eswa.2022.119037

Rafiei Foroushani, M., Tran, D. T. & Iosifidis, A. (2023). Recognition of Defective Mineral Wool Using Pruned ResNet Models. I H. Dorksen, S. Scanzio, J. Jasperneite, L. Wisniewski, K. F. Man, T. Sauter, L. Seno, H. Trsek & V. Vyatkin (red.), 2023 IEEE 21st International Conference on Industrial Informatics (INDIN) IEEE. https://doi.org/10.1109/INDIN51400.2023.10217993

Abkar, M., Zehtabiyan-Rezaie, N. & Iosifidis, A. (2023). Reinforcement learning for wind-farm flow control: Current state and future actions. Theoretical and Applied Mechanics Letters, 13(6), Artikel 100475. https://doi.org/10.1016/j.taml.2023.100475

Cavagna, A., Li, N., Iosifidis, A. & Zhang, Q. (2023). Semantic Communication Enabling Robust Edge Intelligence for Time-Critical IoT Applications. I 2023 IEEE International Conference on Communications Workshops (ICC Workshops) (s. 1617-1622). IEEE. https://doi.org/10.1109/ICCWorkshops57953.2023.10283786

Kakavandi, F., Gomes, C., de Reus, R., Badstue, J., Jensen, J. L., Larsen, P. G. & Iosifidis, A. (2023). Towards Developing a Digital Twin for a Manufacturing Pilot Line: An Industrial Case Study. I E. Karaarslan, Ö. Aydin, Ü. Cali & M. Challenger (red.), Digital Twin Driven Intelligent Systems and Emerging Metaverse (s. 39-64). Springer. https://doi.org/10.1007/978-981-99-0252-1_2

Magris, M. & Iosifidis, A. (2023). Variational Inference for GARCH-family Models. I ICAIF 2023 - 4th ACM International Conference on AI in Finance (s. 541-548). Association for Computing Machinery, Inc.. https://doi.org/10.1145/3604237.3626863

Oleksiienko, I., Tran, D. T. & Iosifidis, A. (2023). Variational Neural Networks. Procedia Computer Science, 222, 104-113. https://doi.org/10.1016/j.procs.2023.08.148

Oleksiienko, I., Nousi, P., Passalis, N., Tefas, A. & Iosifidis, A. (2023). Variational Voxel Pseudo Image Tracking. I 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (s. 323-328). IEEE. https://doi.org/10.1109/SSCI52147.2023.10371810

Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2023). WLD-Reg: A Data-Dependent Within-Layer Diversity Regularizer. I B. Williams, Y. Chen & J. Neville (red.), AAAI-23 Technical Tracks 7 (s. 8421-8429). Artikel 190493 AAAI Press.

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2024). ACCURATE GIGAPIXEL CROWD COUNTING BY ITERATIVE ZOOMING AND REFINEMENT. I ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (s. 6510-6514). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP48485.2024.10446065

Minh Nguyen, Q., Tran, D. T., Kanniainen, J., Iosifidis, A. & Gabbouj, M. (2024). Cryptocurrency Portfolio Optimization by Neural Networks. I 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (s. 25-32). IEEE. https://doi.org/10.1109/SSCI52147.2023.10371855

Pauwels, R. & Iosifidis, A. (2024). Deep Learning in Image Processing: Part 1—Types of Neural Networks, Image Segmentation. I Artificial Intelligence in Dentistry (s. 283-316). Springer. https://doi.org/10.1007/978-3-031-43827-1_17

Pauwels, R. & Iosifidis, A. (2024). Deep Learning in Image Processing: Part 2—Image Enhancement, Reconstruction and Registration. I K. Orhan & R. Jagtap (red.), Artificial Intelligence in Dentistry (s. 317-351). Springer. https://doi.org/10.1007/978-3-031-43827-1_18

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2024). Efficient High-Resolution Deep Learning: A Survey. ACM Computing Surveys, 56(7), 1 - 35. Artikel 181. https://doi.org/10.1145/3645107

Magris, M., Shabani, M. & Iosifidis, A. (2024). Manifold Gaussian Variational Bayes on the Precision Matrix. Neural Computation, 36(9), 1744-1798. https://doi.org/10.1162/neco_a_01686

Angelov, P., Bernardi, M. L., Nardini, F. M., Pecori, R., Valerio, L., Dini, P., Ashraf, S., Aversano, L., Bianchini, M., Brutti, A., Bukovsky, I., Cagnoni, S., Cao, J., Cimitile, M., Dazzi, P., Iammarino, M., Iosifidis, A., Michahelles, F., Mora, A. ... Welsh, M. (2024). PerconAI 2024: 3rd Workshop on Pervasive and Resource-Constrained Artificial Intelligence - Welcome and Committees. I 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (s. 34-35). IEEE. https://doi.org/10.1109/PerComWorkshops59983.2024.10503466

Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2024). Reducing redundancy in the bottleneck representation of autoencoders. Pattern Recognition Letters, 178, 202-208. https://doi.org/10.1016/j.patrec.2024.01.013

Gomes, C., Lucani Rötter, D. E., Iosifidis, A., Feng, H., Ejersbo, H. & Frasheri, M. (2024). Sensing and Communication of Data from the Physical Twin. I J. Fitzgerald, C. Gomes & P. G. Larsen (red.), The Engineering of Digital Twins (s. 147-171). Springer. https://doi.org/10.1007/978-3-031-66719-0_7#citeas

Frasheri, M., Katsaros, P., Iosifidis, A., Hansen, S. T., Gomes, C., Evans, V. T. & Larsen, P. G. (2024). System Monitoring through a Digital Twin. I J. Fitzgerald, C. Gomes & P. G. Larsen (red.), The Engineering of Digital Twins (s. 189-207). Springer. https://doi.org/10.1007/978-3-031-66719-0_9

Oleksiienko, I., Nousi, P., Passalis, N., Tefas, A. & Iosifidis, A. (2024). Vpit: real-time embedded single object 3D tracking using voxel pseudo images. Neural Computing and Applications, 36(32), 20341-20354. https://doi.org/10.1007/s00521-024-10259-2

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Revideret 10.08.2023

Alexandros Iosifidis