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Maysam Behmanesh
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2020 – today
- 2024
- [j3]Maysam Behmanesh
, Peyman Adibi
Cross-modal and multimodal data analysis based on functional mapping of spectral descriptors and manifold regularization. Neurocomputing 598: 128062 (2024) - [j2]Maysam Behmanesh
Geometric Multimodal Deep Learning With Multiscaled Graph Wavelet Convolutional Network. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6991-7005 (2024) - [i5]Maysam Behmanesh, Maks Ovsjanikov:
Smoothed Graph Contrastive Learning via Seamless Proximity Integration. CoRR abs/2402.15270 (2024) - 2023
- [c1]Maysam Behmanesh, Maximilian Krahn, Maks Ovsjanikov:
TIDE: Time Derivative Diffusion for Deep Learning on Graphs. ICML 2023: 2015-2030 - 2022
- [i4]Maximilian Krahn, Maysam Behmanesh, Maks Ovsjanikov:
TIDE: Time Derivative Diffusion for Deep Learning on Graphs. CoRR abs/2212.02483 (2022) - 2021
- [j1]Maysam Behmanesh
Geometric Multimodal Learning Based on Local Signal Expansion for Joint Diagonalization. IEEE Trans. Signal Process. 69: 1271-1286 (2021) - [i3]Maysam Behmanesh
Weighted Least Squares Twin Support Vector Machine with Fuzzy Rough Set Theory for Imbalanced Data Classification. CoRR abs/2105.01198 (2021) - [i2]Maysam Behmanesh
Cross-Modal and Multimodal Data Analysis Based on Functional Mapping of Spectral Descriptors and Manifold Regularization. CoRR abs/2105.05631 (2021) - [i1]Maysam Behmanesh, Peyman Adibi, Sayyed Mohammad Saeed Ehsani, Jocelyn Chanussot:
Geometric Multimodal Deep Learning with Multi-Scaled Graph Wavelet Convolutional Network. CoRR abs/2111.13361 (2021)
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