German Magaj

Publications⁸

• Book Magaj G., Soroka A. A. Advances in Neural Computation, Machine Learning, and Cognitive Research VII Vol. 1120. Studies in Computational Intelligence, 2023. doi
• Chapter Ayzenberg A., Beketov M., Burashnikova A., Magaj G., Polevoi A., Shanin I., Sorokin K. Chordal Embeddings Based on Topology of the Tonal Space, in: Artificial Intelligence in Music, Sound, Art and Design: 12th International Conference, EvoMUSART 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings Vol. 13988. Cham : Springer, 2023. doi Ch. 2. P. 20-33. doi
• Preprint Ayzenberg A., Beketov M., Magaj G. Coverings by open and closed hemispheres / Cornell University. Series arxiv:math.AT "arxiv Algebraic Topology". 2023. doi
• Preprint German Magai. Deep neural networks architectures from the perspective of manifold learning / Cornell University. Series Computer Science "arxiv.org". 2023. (in press)
• Chapter Magai German, Soroka A. Estimating the Transfer Learning Ability of a Deep Neural Networks by Means of Representations, in: Advances in Neural Computation, Machine Learning, and Cognitive Research VII Vol. 1120. Studies in Computational Intelligence, 2023. doi doi
• Preprint Sorokin K., Зайцев А. В., Левин А. М., Magaj G., Beketov M., Sotskov V. Global cognitive graph properties dynamics of hippocampal formation / Cornell University. Series arxiv:q-bio.NC "arxiv Quantitative Biology". 2023. doi
• Article Magaj G. ICML 2023 Topological Deep Learning Challenge: Design and Results // Proceedings of Machine Learning Research. 2023. Vol. 221. No. 3. P. 1-6. doi
• Preprint Magai German, Ayzenberg A. Topology and geometry of data manifold in deep learning / Cornell University . Series CS "https://arxiv.org/". 2022. doi