289 citations · 1.7k across the 90 of their papers we have counts for
14 papers · 1 filter
Self-supervised Learning of Dense Shape Correspondence
Oshri Halimi, Or Litany, Emanuele Rodolà +2
We introduce the first completely unsupervised correspondence learning approach for deformable 3D shapes. Key to our model is the understanding that natural deformations (such as c…
Learning beamforming in ultrasound imaging
Sanketh Vedula, Ortal Senouf, Grigoriy Zurakhov +3
Medical ultrasound (US) is a widespread imaging modality owing its popularity to cost efficiency, portability, speed, and lack of harmful ionizing radiation. In this paper, we demo…
Efficient non-uniform quantizer for quantized neural network targeting reconfigurable hardware
Natan Liss, Chaim Baskin, Avi Mendelson +2
Convolutional Neural Networks (CNN) has become more popular choice for various tasks such as computer vision, speech recognition and natural language processing. Thanks to their la…
SGR: Self-Supervised Spectral Graph Representation Learning
Anton Tsitsulin, Davide Mottin, Panagiotis Karras +2
Representing a graph as a vector is a challenging task; ideally, the representation should be easily computable and conducive to efficient comparisons among graphs, tailored to the…
NICE: Noise Injection and Clamping Estimation for Neural Network Quantization
Chaim Baskin, Natan Liss, Yoav Chai +5
Convolutional Neural Networks (CNN) are very popular in many fields including computer vision, speech recognition, natural language processing, to name a few. Though deep learning…
Functional Maps Representation on Product Manifolds
Emanuele Rodolà, Zorah Lähner, Alex M. Bronstein +2
We consider the tasks of representing, analyzing and manipulating maps between shapes. We model maps as densities over the product manifold of the input shapes; these densities can…