Ivanov P., Shtark M., Kozhevnikov A., Golyadkin M., Botov D., Makarov I. SensorDBSCAN: Semi-Supervised Active Learning Powered Method for Anomaly Detection and Diagnosis. IEEE Access. 2025. Vol. 13. pp. 25186-25197.
Shtark M., Kozhevnikov A., Ivanov P., Makarov I. Poster Abstract: Minimizing Labeling Efforts for Fault Detection and Diagnosis. SenSys '25: Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems. 2025. pp. 666-667.
Ivanov P., Kozhevnikov A., Shtark M., Makarov I. Poster Abstract: Exploring the Autoencoder Sequence Pooling. SenSys '25: Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems. 2025. pp. 606-607.
Makarov I. Pose Networks Unveiled: Bridging the Gap for Monocular Depth Perception. 2024 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). 2024. pp. 584-587.
Golyadkin M., Shtark M., Ivanov P., Kozhevnikov A., Zhukov L., Makarov I. Plug-and-Play Unsupervised Fault Detection and Diagnosis for Complex Industrial Monitoring. 33th International Joint Conference on Artificial Intelligence, IJCAI 2024. 2024. pp. 8669-8673.
Makarov I. LLM-KT: A Versatile Framework for Knowledge Transfer from Large Language Models to Collaborative Filtering. 2024 IEEE International Conference on Data Mining Workshops (ICDMW). 2024. pp. 903-906.
Makarov I. Adversarial Attacks and Defenses in Fault Detection and Diagnosis: A Comprehensive Benchmark on the Tennessee Eastman Process. IEEE Open Journal of the Industrial Electronics Society. 2024. pp. 428 - 440.
Gambashidze A., Dadukin A., Golyadkin M., Razzhivina M., Makarov I. Weak-to-Strong 3D Object Detection with X-Ray Distillation. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2024. pp. 15055–15064.
Mozikov M., Severin N., Bodishtianu V., Glushanina M., Nasonov I., Orekhov D., Pekhotin V., Makovetskiy I., Baklashkin M., Lavrentyev V., Tsvigun A., Turdakov D., Shavrina T., Savchenko A., Makarov I. EAI: Emotional Decision-Making of LLMs in Strategic Games and Ethical Dilemmas. Advances in Neural Information Processing Systems. 2024. Vol. 37. pp. 1-15.
Pozdnyakov V., Kovalenko A., Makarov I., Drobyshevskiy M., Lukyanov K. AADMIP: Adversarial Attacks and Defenses Modeling in Industrial Processes. Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence. 2024. pp. 8776--8779.
Gerasyov M., Kiselev D., Beketov M., Makarov I. VIA AI: Reliable Deep Reinforcement Learning for Traffic Signal Control. 2024 IEEE International Conference on Data Mining Workshops (ICDMW). 2024. pp. 887-890.
Gerasimova O., Severin N., Makarov I. Comparative Analysis of Logic Reasoning and Graph Neural Networks for Ontology-Mediated Query Answering With a Covering Axiom. IEEE Access. 2023. Vol. 11. pp. 88074-88086.
Макаров И.А. MonoVAN: Visual Attention for Self-Supervised Monocular Depth Estimation. IEEE. 2023.
Макаров И.А. Predicting Molecule Toxicity via Descriptor-based Graph Self-supervised Learning. IEEE Access. 2023. pp. 91842 - 91849.
Semenkov I., Fedosov N., Makarov I., Ossadtchi A. Real-time low latency estimation of brain rhythms with deep neural networks. Journal of Neural Engineering. 2023. Vol. 20. No. 5. pp. 056008.
Gerasyov M., Makarov I. Dealing With Sparse Rewards Using Graph Neural Networks. IEEE Access. 2023. Vol. 11. pp. 89180-89187.
Luginov A., Makarov I. SwiftDepth: An Efficient Hybrid CNN-Transformer Model for Self-Supervised Monocular Depth Estimation on Mobile Devices. 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). 2023. pp. 642-647.
Макаров И.А. Temporal network embedding framework with causal anonymous walks representations. PeerJ Computer Science. 2022.
Макаров И.А. SensorSCAN: Self-Supervised Learning and Deep Clustering for Fault Diagnosis in Chemical Processes. Artificial Intelligence. 2022.
Kiselev D., Makarov I. Exploration in Sequential Recommender Systems via Graph Representations. IEEE Access. 2022. Vol. 10. pp. 123614-123621.
Макаров И.А. Exploring Efficiency of Vision Transformers for Self-Supervised Monocular Depth Estimation. IEEE. 2022. pp. 711-719.
Savchenko A., Makarov I., Savchenko L.V. Classifying emotions and engagement in online learning based on a single facial expression recognition neural network. IEEE Transactions on Affective Computing. 2022. Vol. 13. No. 4. pp. 2132-2143.
Makarov I., Korovina K., Kiselev D. JONNEE: Joint Network Nodes and Edges Embedding. IEEE Access. 2021. Vol. 9. pp. 144646-144659.
Макаров И.А. Depth Inpainting via Vision Transformer. IEEE. 2021.
Корея, Республика
Российская Федерация, Москва
Российская Федерация, Москва