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Глава в книге
Pre-trained LLMs Meet Sequential Recommenders: Efficient U ser-CentricKnowledgeDistillation

Severin N., Kartushov D., Urzhumov V. et al.

In bk.: Advances in Information Retrieval: 48th European Conference on Information Retrieval, ECIR 2026, Delft, The Netherlands, March 29 – April 2, 2026, Proceedings, Part II. (LNCS, volume 16484). Cham: Springer Publishing Company, 2026. P. 508-517.

Препринт
Hessian-based lightweight neural network for brain vessel segmentation on a minimal training dataset

Меньшиков И. А., Бернадотт А. К., Elvimov N. S.

Statistical mechanics. arXie. arXive, 2025

Analysis and Visualization of Networks

2025/2026
Учебный год
ENG
Обучение ведется на английском языке
4
Кредиты
Статус:
Курс обязательный
Когда читается:
4-й курс, 3 модуль

Преподаватель

Course Syllabus

Abstract

This course introduces methods and algorithms for analysing and visualizing graphs and networks. The course includes a review of modern network analysis and visualization techniques with their applications in various domains. We will concern on three main topics: network analysis methods based on applied graph theory, graph drawing algorithms, applications of network analysis and visualization to real problems.