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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Understanding the Electric Double Layer at the Electrode-Electrolyte Interface: Part I – No Ion Specific Adsorption

ChemPhysChem. 2024. Vol. 25. No. 23. Article e20240065050.
Mazur D., Petr E. Brandyshev, Doronin S. V., Budkov Y.

We present a comprehensive mean-field model that takes into account the key components of modern electrical double layer theory at the interface between an electrode and an electrolyte solution. The model considers short-range specific interactions between different species, including electrode-ion repulsion, the hydration of ions, dielectric saturation of solvent (water), and excluded volume (steric) interactions between species. By solving a modified Poisson-Boltzmann equation and using the appropriate results of quantum chemistry calculations on the hydration of ions, we can accurately approximate the differential capacitance profiles of aqueous electrolyte solutions at the boundary with a silver electrode. The specific interactions between the ions and the electrodes in the systems under consideration are assumed to be significantly weaker than their Coulomb interactions. A novel aspect of our research is the investigation of the impact of short-range ion-water interactions on the differential capacitance, which provides new insights into the behavior of the electrical double layer. This model holds the potential to be useful for electrochemical engineers working on the development of supercapacitors and related electrochemical energy storage devices. It serves as a basis for future modeling of electrolyte systems on real electrodes, especially in scenarios where chemical ion-electrode interactions are significant.

Research target: Chemistry Electronics and Electrical Engineering Physics
Language: English
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Keywords: двойной электрический слойsupercapacitorsElectric double layerelectrolytesэлектролитыMean FieldСуперконденсаторытеория среднего поляElectric differential capacitanceДифференциальная электрическая ёмкость
Publication based on the results of:
Прогнозирование свойств молекулярных систем: совмещение методов машинного обучения и классических методов моделирования (2026)
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