5 papers · 1 filter
Learning a non-linguistic code for inferred rules from reward
Cristiano Capone
How can a rule inferred from examples reach someone who never saw them, without a shared code? Patients with severe aphasia do it by gesture or sketch. One network sees worked exam…
Bilinear gating of motor primitives: a principle linking dendritic computation to rapid goal-directed adaptation
Cristiano Capone, Luca Falorsi, Andrea Ciardiello +1
Movement requires the motor cortex to specify both \emph{what} action to produce and \emph{which goal} it serves, yet how individual neurons separate these factors is not understoo…
Unified Policy Value Decomposition for Rapid Adaptation
Cristiano Capone, Luca Falorsi, Andrea Ciardiello +1
Rapid adaptation in complex control systems remains a central challenge in reinforcement learning. We introduce a framework in which policy and value functions share a low-dimensio…
Training slow silicon neurons to control extremely fast robots with spiking reinforcement learning
Irene Ambrosini, Ingo Blakowski, Dmitrii Zendrikov +5
Air hockey demands split-second decisions at high puck velocities, a challenge we address with a compact network of spiking neurons running on a mixed-signal analog/digital neuromo…
Lightweight Test-Time Adaptation for EMG-Based Gesture Recognition
Nia Touko, Matthew O A Ellis, Cristiano Capone +3
Reliable long-term decoding of gestures from surface electromyography (EMG) is hindered by signal drift caused by electrode displacement, muscle fatigue, and/or posture changes. Al…