1 citations · 1 across the 1 of their papers we have counts for
4 papers
How to Train Your Resistive Network: Generalized Equilibrium Propagation and Analytical Learning
Jonathan Lin, Aman Desai, Frank Barrows +1
Machine learning is a powerful method of extracting meaning from data; unfortunately, current digital hardware is extremely energy-intensive. There is interest in an alternative an…
A unifying approach to self-organizing systems interacting via conservation laws
Frank Barrows, Guanming Zhang, Satyam Anand +5
We present a unified framework for embedding and analyzing dynamical systems using generalized projection operators rooted in local conservation laws. By representing physical, bio…
Voltage-Controlled Oscillator and Memristor-Based Analog Computing for Solving Systems of Linear Equations
Hao Li, Rizwan S. Peerla, Frank Barrows +2
Matrix computations have become increasingly significant in many data-driven applications. However, Moores law for digital computers has been gradually approaching its limit in rec…
R-Ising: Effective resistance in random magnetic nanowires networks
Frank Barrows, Ezio Iacocca, Francesco Caravelli
Random assemblies of magnetic nanowires represent a unique class of materials with promising applications in spintronics and information storage. These assemblies exhibit complex b…