Работы, цитирующие эту работу

Работ: 5

Работа: Geometric Deep Learning: Going beyond Euclidean data

1. Learning Graph-Convolutional Representations for Point Cloud Denoising

   Francesca Pistilli, Giulia Fracastoro, Diego Valsesia +1

   Препринт3D Shape Modeling and AnalysisLecture notes in computer science2020Цитирований: 0

   ABIABI:AkademIndex/openalex/2020.preprint.000007

2. A Laplacian-based quantum graph neural networks for quantum semi-supervised learning

   Hamed Gholipour, Farid Bozorgnia, Kailash Hambarde +6

   СтатьяQuantum Computing Algorithms and ArchitectureQuantum Information Processing2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.002792

3. Fractional Heat Kernel for Semi-Supervised Graph Learning with Small Training Sample Size

   Farid Bozorgnia, Vyacheslav Kungurtsev, Shirali Kadyrov +1

   ПрепринтNeural Networks and ApplicationsSSRN Electronic Journal2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.preprint.000308

4. Fractional Heat Kernel for Semi-Supervised Graph Learning with Small Training Sample Size

   Farid Bozorgnia, Vyacheslav Kungurtsev, Shirali Kadyrov +1

   ПрепринтNeural Networks and ApplicationsSSRN Electronic Journal2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.preprint.000338

5. Robustness of Spectral–Geometric Invariants Under Realistic 3D Acquisition Distortions: A Critical Review, Taxonomy, and Comparative Evaluation Protocol

   J. X. Djumanov, Temur Khudayberganov

   Препринт3D Shape Modeling and AnalysisResearch Square2026Цитирований: 0

   ABIABI:AkademIndex/openalex/2026.preprint.000105