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ORCIDAlexander Kovalenko
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- 2026
[i6]Alexander Kovalenko:
CASCADE: Cross-scale Advective Super-resolution with Climate Assimilation and Downscaling Evolution. CoRR abs/2603.00109 (2026)- 2025
- [c9]Karel Charvát, Stein-Runar Bergheim, Raúl Palma, Adam Aron Rynkiewicz
, Matús Botek, Alexander Kovalenko, Pavel Kordík, Antonín Kubícek, Markéta Kollerová, Sárka Horáková:
Bridging Global Language Models and Local Spatial Data: The JackDaw Approach to Context-Aware Agriculture and Rural Planning. FedCSIS 2025: 507-518 - [c8]Tommy Chu, Alexander Kovalenko:
Projective Pruning for Decoupling Weights. ECML/PKDD (6) 2025: 322-339 - [c7]Matej Jech, Gabriele Maria Grittani, Carlo Maria Lazzarini, Alexander Kovalenko:
Denoising Diffusion Implicit Models for Laser-Plasma Accelerator Simulation Trained With Physical Constraint Loss. ECML/PKDD (8) 2025: 422-437 - [i5]Eddi Weinwurm, Alexander Kovalenko:
Preserving Vector Space Properties in Dimensionality Reduction: A Relationship Preserving Loss Framework. CoRR abs/2509.01198 (2025) - 2024
- [j2]Frantisek Koutenský, Petr Simánek, Miroslav Cepek, Alexander Kovalenko:
Overcoming Long Inference Time of Nearest Neighbors Analysis in Regression and Uncertainty Prediction. SN Comput. Sci. 5(5): 486 (2024) - [c6]Jirí Pihrt, Petr Simánek, Alexander Kovalenko, Jirí Kvapil, Karel Charvát:
AI-Based Spatiotemporal Crop Monitoring by Cloud Removal in Satellite Images. FedCSIS 2024: 485-492 - [c5]Jakub Horenin, Veronika Magdanz, Islam S. M. Khalil, Anke Klingner, Alexander Kovalenko, Miroslav Cepek:
Machine Learning Based Tool for Automated Sperm Cell Tracking and Sperm Bundle Detection. ECML/PKDD (10) 2024: 19-32 - 2023
- [c4]Alexander Kovalenko, Pavel Kordík:
Decorelated Weight Initialization by Backpropagation. ICANN (1) 2023: 546-550 - 2022
- [c3]Uladzislau Yorsh, Alexander Kovalenko:
Linear Self-attention Approximation via Trainable Feedforward Kernel. ICANN (3) 2022: 807-810 - [i4]Alexander Kovalenko, Vitaliy Pozdnyakov, Ilya Makarov:
Graph Neural Networks with Trainable Adjacency Matrices for Fault Diagnosis on Multivariate Sensor Data. CoRR abs/2210.11164 (2022) - [i3]Uladzislau Yorsh, Alexander Kovalenko:
Linear Self-Attention Approximation via Trainable Feedforward Kernel. CoRR abs/2211.04076 (2022) - 2021
- [j1]Petr Maj, Konrad Siek, Alexander Kovalenko, Jan Vitek:
CodeDJ: Reproducible Queries over Large-Scale Software Repositories (Artifact). Dagstuhl Artifacts Ser. 7(2): 13:1-13:4 (2021) - [c2]Petr Maj, Konrad Siek, Alexander Kovalenko, Jan Vitek:
CodeDJ: Reproducible Queries over Large-Scale Software Repositories. ECOOP 2021: 6:1-6:24 - [c1]Alexander Kovalenko, Pavel Kordík, Magda Friedjungová:
Dynamic Neural Diversification: Path to Computationally Sustainable Neural Networks. ICANN (2) 2021: 235-247 - [i2]Alexander Kovalenko, Pavel Kordík, Magda Friedjungová:
Dynamic Neural Diversification: Path to Computationally Sustainable Neural Networks. CoRR abs/2109.09612 (2021) - [i1]Uladzislau Yorsh, Alexander Kovalenko:
Pureformer: Do We Even Need Attention? CoRR abs/2111.15588 (2021)
Coauthor Index
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