3 citations · 5 across the 5 of their papers we have counts for
6 papers
Learning Associations in Reconfigurable Particle Packings via Local Cyclic Driving
Wenjing Guo, Vidyesh Rao Anisetti, Kairui Zhang +7
We investigate associative-memory behavior in a reconfigurable particle packing programmed by purely local cyclic driving. The system is a two-dimensional bidisperse Lennard--Jones…
Rectification of Random Walkers Induced by Energy Flow at Boundaries
Vidyesh Rao Anisetti, Sharath Ananthamurthy, J. M. Schwarz
We explore rectification phenomena in a system where two-dimensional random walkers interact with a funnel-shaped ratchet under two distinct classes of reflection rules. The two cl…
Emergent learning in physical systems as feedback-based aging in a glassy landscape
Vidyesh Rao Anisetti, Ananth Kandala, J. M. Schwarz
By training linear physical networks to learn linear transformations, we discern how their physical properties evolve due to weight update rules. Our findings highlight a striking…
A slime mold inspired local adaptive mechanism for flow networks
Vidyesh Rao Anisetti, Ananth Kandala, J. M. Schwarz
In the realm of biological flow networks, the ability to dynamically adjust to varying demands is paramount. Drawing inspiration from the remarkable adaptability of Physarum polyce…
Frequency propagation: Multi-mechanism learning in nonlinear physical networks
Vidyesh Rao Anisetti, A. Kandala, B. Scellier +1
We introduce frequency propagation, a learning algorithm for nonlinear physical networks. In a resistive electrical circuit with variable resistors, an activation current is applie…
Learning by non-interfering feedback chemical signaling in physical networks
Vidyesh Rao Anisetti, B. Scellier, J. M. Schwarz
Both non-neural and neural biological systems can learn. So rather than focusing on purely brain-like learning, efforts are underway to study learning in physical systems. Such eff…