activity
20172022
most citedPower-law Scaling to Assist with Key Challenges in Artificial Intelligence

22 citations · 43 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG202222 cited

Power-law Scaling to Assist with Key Challenges in Artificial Intelligence

Yuval Meir, Shira Sardi, Shiri Hodassman +4

Power-law scaling, a central concept in critical phenomena, is found to be useful in deep learning, where optimized test errors on handwritten digit examples converge as a power-la…

q-bio.NC20208 cited

Brain experiments imply adaptation mechanisms which outperform common AI learning algorithms

Shira Sardi, Roni Vardi, Yuval Meir +4

Attempting to imitate the brain functionalities, researchers have bridged between neuroscience and artificial intelligence for decades; however, experimental neuroscience has not d…

q-bio.NC20175 cited

Vitality of Neural Networks under Reoccurring Catastrophic Failures

Shira Sardi, Amir Goldental, Hamutal Amir +2

Catastrophic failures are complete and sudden collapses in the activity of large networks such as economics, electrical power grids and computer networks, which typically require a…

q-bio.NC20178 cited

Fast Reversible Learning based on Neurons functioning as Anisotropic Multiplex Hubs

Roni Vardi, Amir Goldental, Anton Sheinin +2

Neural networks are composed of neurons and synapses, which are responsible for learning in a slow adaptive dynamical process. Here we experimentally show that neurons act like ind…

q-bio.NC2017

Oscillations in networks of networks stem from adaptive nodes with memory

Amir Goldental, Herut Uzan, Shira Sardi +1

We present an analytical framework that allows the quantitative study of statistical dynamic properties of networks with adaptive nodes that have memory and is used to examine the…