12 citations · 12 across the 8 of their papers we have counts for
8 papers
Direct and inverse cascades scaling in real shell models of turbulence
James Creswell, Viatcheslav Mukhanov, Yaron Oz
Shell models provide a simplified mathematical framework that captures essential features of incompressible fluid turbulence, such as the energy cascade and scaling of the fluid ob…
Input Space Mode Connectivity in Deep Neural Networks
Jakub Vrabel, Ori Shem-Ur, Yaron Oz +1
We extend the concept of loss landscape mode connectivity to the input space of deep neural networks. Mode connectivity was originally studied within parameter space, where it desc…
Gravitationally dominated instantons and instability of dS, AdS and Minkowski spaces
Viatcheslav F. Mukhanov, Yaron Oz, Alexander S. Sorin
We study the decay of the false vacuum in the regime where the quantum field theory analysis is not valid, since gravitational effects become important. This happens when the heigh…
Holographic Turbulence From a Random Gravitational Potential
Yaron Oz, Sebastian Waeber, Amos Yarom
We study the turbulent dynamics of a relativistic (2 + 1)-dimensional fluid placed in a stochastic gravitational potential. We demonstrate that the dynamics of the fluid can be obt…
Anomalous scaling in shell model turbulence
James Creswell, Viatcheslav Mukhanov, Yaron Oz
Shell model turbulence is a simplified mathematical framework that captures essential features of incompressible fluid turbulence such as the energy cascade, intermittency and anom…
Weak Correlations as the Underlying Principle for Linearization of Gradient-Based Learning Systems
Ori Shem-Ur, Khen Cohen, Aviv Orly +1
Deep learning models, such as wide neural networks, can be conceptualized as nonlinear dynamical physical systems characterized by a multitude of interacting degrees of freedom. Su…
The Universal Statistical Structure and Scaling Laws of Chaos and Turbulence
Noam Levi, Yaron Oz
Turbulence is a complex spatial and temporal structure created by the strong non-linear dynamics of fluid flows at high Reynolds numbers. Despite being an ubiquitous phenomenon tha…
Turbulence Scaling from Deep Learning Diffusion Generative Models
Tim Whittaker, Romuald A. Janik, Yaron Oz
Complex spatial and temporal structures are inherent characteristics of turbulent fluid flows and comprehending them poses a major challenge. This comprehesion necessitates an unde…