34 citations · 69 across the 9 of their papers we have counts for
3 papers · 1 filter
Microscopic imprints of learned solutions in adaptive resistor networks
Marcel Guzman, Felipe Martins, Menachem Stern +1
In physical networks trained using supervised learning, physical parameters are adjusted to produce desired responses to inputs. An example is electrical contrastive local learning…
Cornerstones are the Key Stones: Using Interpretable Machine Learning to Probe the Clogging Process in 2D Granular Hoppers
Jesse M. Hanlan, Sam Dillavou, Andrea J. Liu +1
The sudden arrest of flow by formation of a stable arch over an outlet is a unique and characteristic feature of granular materials. Previous work suggests that grains near the out…
Physical networks become what they learn
Menachem Stern, Marcelo Guzman, Felipe Martins +2
Physical networks can develop diverse responses, or functions, by design, evolution or learning. We focus on electrical networks of nodes connected by resistive edges. Such network…