German Magai

According to our database, German Magai authored at least 9 papers between 2022 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Artificial Text Boundary Detection with Topological Data Analysis and Sliding Window Techniques.

Laida Kushnareva, Tatiana Gaintseva, German Magai, Serguei Barannikov, Dmitry Abulkhanov, Kristian Kuznetsov, Irina Piontkovskaya, Sergey I. Nikolenko

CoRR, 2023

ICML 2023 Topological Deep Learning Challenge : Design and Results.

Mathilde Papillon, Mustafa Hajij, Florian Frantzen, Josef Hoppe, Helen Jenne, Johan Mathe, Audun Myers, Theodore Papamarkou, Michael T. Schaub, Ghada Zamzmi, Tolga Birdal, Tamal K. Dey, Tim Doster, Tegan Emerson, Gurusankar Gopalakrishnan, Devendra Govil, Vincent P. Grande, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Jan Meissner, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn, Michael Scholkemper, Robin Walters, Jens Agerberg, Georg Bökman, Sadrodin Barikbin, Claudio Battiloro, Gleb Bazhenov, Guillermo Bernárdez, Aiden Brent, Sergio Escalera, Simone Fiorellino, Dmitrii Gavrilev, Mohammed Hassanin, Paul Häusner, Odin Hoff Gardaa, Abdelwahed Khamis, Manuel Lecha, German Magai, Tatiana Malygina, Pavlo Melnyk, et al.

CoRR, 2023

Global cognitive graph properties dynamics of hippocampal formation.

Konstantin Sorokin, Andrey Zaitsev, Aleksandr Levin, German Magai, Maxim Beketov, Vladimir Sotskov

CoRR, 2023

Applying language models to algebraic topology: generating simplicial cycles using multi-labeling in Wu's formula.

Kirill Brilliantov, Fedor Pavutnitskiy, Dmitry Pasechnyuk, German Magai

CoRR, 2023

Deep neural networks architectures from the perspective of manifold learning.

German Magai

CoRR, 2023

Explaining the Transfer Learning Ability of a Deep Neural Networks by Means of Representations.

German Magai, Artem Soroka

Proceedings of the Joint Proceedings of the xAI-2023 Late-breaking Work, 2023

ICML 2023 Topological Deep Learning Challenge: Design and Results.

Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane

Proceedings of the Topological, 2023

Chordal Embeddings Based on Topology of the Tonal Space.

Anton Ayzenberg, Maxim Beketov, Aleksandra Burashnikova, German Magai, Anton Polevoi, Ivan Shanin, Konstantin Sorokin

Proceedings of the Artificial Intelligence in Music, Sound, Art and Design, 2023

2022

Topology and geometry of data manifold in deep learning.

German Magai, Anton Ayzenberg

CoRR, 2022