2 citations · 2 across the 6 of their papers we have counts for
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cs.CV2025
Learning Eigenstructures of Unstructured Data Manifolds
Roy Velich, Arkadi Piven, David Bensaïd +3
We introduce a novel framework that directly learns a spectral basis for shape and manifold analysis from unstructured data, eliminating the need for traditional operator selection…
cs.AI2025
SingLoRA: Low Rank Adaptation Using a Single Matrix
David Bensaïd, Noam Rotstein, Roy Velich +2
Low-Rank Adaptation (LoRA) has significantly advanced parameter-efficient fine-tuning of large pretrained models. LoRA augments the pre-trained weights of a model by adding the pro…
cs.CV2025
Neural Descriptors: Self-Supervised Learning of Robust Local Surface Descriptors Using Polynomial Patches
Gal Yona, Roy Velich, Ron Kimmel +1
Classical shape descriptors such as Heat Kernel Signature (HKS), Wave Kernel Signature (WKS), and Signature of Histograms of OrienTations (SHOT), while widely used in shape analysi…