1 citations · 1 across the 4 of their papers we have counts for
4 papers
Curvature Enhanced Data Augmentation for Regression
Ilya Kaufman Sirot, Omri Azencot
Deep learning models with a large number of parameters, often referred to as over-parameterized models, have achieved exceptional performance across various tasks. Despite concerns…
Analyzing Deep Transformer Models for Time Series Forecasting via Manifold Learning
Ilya Kaufman, Omri Azencot
Transformer models have consistently achieved remarkable results in various domains such as natural language processing and computer vision. However, despite ongoing research effor…
First-Order Manifold Data Augmentation for Regression Learning
Ilya Kaufman, Omri Azencot
Data augmentation (DA) methods tailored to specific domains generate synthetic samples by applying transformations that are appropriate for the characteristics of the underlying da…
Data Representations' Study of Latent Image Manifolds
Ilya Kaufman, Omri Azencot
Deep neural networks have been demonstrated to achieve phenomenal success in many domains, and yet their inner mechanisms are not well understood. In this paper, we investigate the…