54 citations · 105 across the 17 of their papers we have counts for
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cs.LG2023★ 11 cited
Reverse Engineering Self-Supervised Learning
Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti +2
Self-supervised learning (SSL) is a powerful tool in machine learning, but understanding the learned representations and their underlying mechanisms remains a challenge. This paper…
cs.LG2023
Numerical Methods For PDEs Over Manifolds Using Spectral Physics Informed Neural Networks
Yuval Zelig, Shai Dekel
We introduce an approach for solving PDEs over manifolds using physics informed neural networks whose architecture aligns with spectral methods. The networks are trained to take in…
cs.LG2023★ 1 cited
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions
Ido Ben-Shaul, Tomer Galanti, Shai Dekel
Multiplication layers are a key component in various influential neural network modules, including self-attention and hypernetwork layers. In this paper, we investigate the approxi…