Research output per year
Research output per year
Personal profile
Artistic and research interests
Doctoral Researcher
Department of Computer Science
I am working on deep learning applications in science and engineering. My research lies in the intersection of partial differential equations and deep neural networks, more information can he found here .
Education/Academic qualification
Tekn. toht., tietotekniikka
Award Date: 26 May 2025
Keywords
- Neural networks
- Deep learning
- Partial differential equations
- Modelling
Fingerprint
Dive into the research topics where Katsiaryna Haitsiukevich is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Advances in physics-informed deep learning
Haitsiukevich, K., 2025, Aalto University. 134 p.Research output: Thesis › Doctoral Thesis › Collection of Articles
Open Access -
Diffusion models as probabilistic neural operators for recovering unobserved states of dynamical systems
Haitsiukevich, K., Poyraz, O., Marttinen, P. & Ilin, A., Sept 2024, 34th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2024 - Proceedings. IEEE, 6 p. ( IEEE International Workshop on Machine Learning for Signal Processing).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
Open AccessFile1 Citation (Scopus)33 Downloads (Pure) -
In-Context Symbolic Regression : Leveraging Large Language Models for Function Discovery
Merler, M., Haitsiukevich, K., Dainese, N. & Marttinen, P., 2024, Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop). Fu, X. & Fleisig, E. (eds.). Association for Computational Linguistics, p. 589-606 18 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics; vol. 4).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
Open Access -
Improved Training of Physics-Informed Neural Networks with Model Ensembles
Haitsiukevich, K. & Ilin, A., 2023, IJCNN 2023 - International Joint Conference on Neural Networks, Proceedings. IEEE, (Proceedings of International Joint Conference on Neural Networks).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
Open Access11 Citations (Scopus) -
Learning Trajectories of Hamiltonian Systems with Neural Networks
Haitsiukevich, K. & Ilin, A., 7 Sept 2022, Artificial Neural Networks and Machine Learning – ICANN 2022. Pimenidis, E., Aydin, M., Angelov, P., Jayne, C. & Papaleonidas, A. (eds.). Bristol, UK: Springer, p. 562–573 12 p. (Lecture Notes in Computer Science; vol. 13529).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
Open AccessFile1 Citation (Scopus)52 Downloads (Pure)
Activities
- 3 Conference presentation
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Diffusion Models as Probabilistic Neural Operators for Recovering Unobserved States of Dynamical Systems
Haitsiukevich, K. (Speaker)
Sept 2024Activity: Talk or presentation types › Conference presentation
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Improved Training of Physics-Informed Neural Networks with Model Ensembles
Haitsiukevich, K. (Speaker)
Jun 2023Activity: Talk or presentation types › Conference presentation
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Learning Trajectories of Hamiltonian Systems with Neural Networks
Haitsiukevich, K. (Speaker) & Ilin, A. (Speaker)
7 Sept 2022Activity: Talk or presentation types › Conference presentation