Prediction of New Itinerary Markets for Airlines via Network Embedding. - Dmitrii Kiselev; Ilya Makarov (AIST (Supplement), 2019)

JONNEE: Joint Network Nodes and Edges Embedding. - Ilya Makarov; Ksenia Korovina; Dmitrii Kiselev (IEEE Access, 2021)

Survey on graph embeddings and their applications to machine learning problems on graphs. - Ilya Makarov; Dmitrii Kiselev; Nikita Nikitinsky; Lovro Subelj (PeerJ Comput. Sci., 2021)

Fusion of text and graph information for machine learning problems on networks. - Ilya Makarov; Mikhail Makarov; Dmitrii Kiselev (PeerJ Comput. Sci., 2021)

Exploration in Sequential Recommender Systems via Graph Representations. - Dmitrii Kiselev; Ilya Makarov (IEEE Access, 2022)

Temporal network embedding framework with causal anonymous walks representations. - Ilya Makarov; Andrey V. Savchenko; Arseny Korovko; Leonid Sherstyuk; Nikita Severin; Dmitrii Kiselev; Aleksandr Mikheev; Dmitrii Babaev (PeerJ Comput. Sci., 2022)

Ti-DC-GNN: Incorporating Time-Interval Dual Graphs for Recommender Systems. - Nikita Severin; Andrey V. Savchenko; Dmitrii Kiselev; Maria Ivanova; Ivan Kireev; Ilya Makarov (RecSys, 2023)

Predicting Molecule Toxicity via Descriptor-Based Graph Self-Supervised Learning. - Xinze Li; Ilya Makarov; Dmitrii Kiselev (IEEE Access, 2023)

VIA AI: Reliable Deep Reinforcement Learning for Traffic Signal Control. - Matvey Gerasyov; Dmitrii Kiselev; Maxim Beketov; Ilya Makarov (ICDM (Workshops), 2024)

LLM-KT: A Versatile Framework for Knowledge Transfer from Large Language Models to Collaborative Filtering. - Nikita Severin; Aleksei Ziablitsev; Yulia Savelyeva; Valeriy Tashchilin; Ivan Bulychev; Mikhail Yushkov; Artem Kushneruk; Amaliya Zaryvnykh; Dmitrii Kiselev; Andrey V. Savchenko; Ilya Makarov (ICDM (Workshops), 2024)