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- Moscow Institute of Physics and TechnologyRU2 papers
- Accenture (Switzerland)CH1 paper
- Astana Medical UniversityKZ1 paper
- Clinical Institute of BrainRU1 paper
- École des hautes études en sciences socialesFR1 paper
- Federal State Budgetary Institution Russian Scientific Center of RoentgenoradiologyRU1 paper
- Huawei Technologies (China)CN1 paper
- Independent University of MoscowRU1 paper
- Indian Institute of Technology BombayIN1 paper
- Institut CurieFR1 paper
- Institute of Molecular Biology and GeneticsUA1 paper
- International University of KyrgyzstanKG1 paper
Showing cs.LGShow all
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cs.LG2026
CayleyPy RL: Pathfinding and Reinforcement Learning on Cayley Graphs
A. Chervov, M. Obozov, A. Soibelman +31
This paper is the second in a series of studies on developing efficient artificial intelligence-based approaches to pathfinding on extremely large graphs (e.g. nodes) wit…
cs.LG2026
How Long short-term memory artificial neural network, synthetic data, and fine-tuning improve the classification of raw EEG data
Albert Nasybullin, Vladimir Maksimenko, Semen Kurkin
In this paper, we discuss a Machine Learning pipeline for the classification of EEG data. We propose a combination of synthetic data generation, long short-term memory artificial n…
cs.LG2026
Convolutional Neural Network and Adversarial Autoencoder in EEG images classification
Albert Nasybullin, Semen Kurkin
In this paper, we consider applying computer vision algorithms for the classification problem one faces in neuroscience during EEG data analysis. Our approach is to apply a combina…