22 citations · 50 across the 7 of their papers we have counts for
7 papers
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…
Significant anisotropic neuronal refractory period plasticity
Roni Vardi, Yael Tugendhaft, Shira Sardi +1
Refractory periods are an unavoidable feature of excitable elements, resulting in necessary time-lags for re-excitation. Herein, we measure neuronal absolute refractory periods (AR…
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…
Embedding information in physically generated random bit sequences while maintaining certified randomness
Shira Sardi, Herut Uzan, Shiri Otmazgin +3
Ultrafast physical random bit generation at hundreds of Gb/s rates, with verified randomness, is a crucial ingredient in secure communication and have recently emerged using optics…
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…
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…