2 papers
cs.LG2019
Improving Coordination in Small-Scale Multi-Agent Deep Reinforcement Learning through Memory-driven Communication
Emanuele Pesce, Giovanni Montana
Deep reinforcement learning algorithms have recently been used to train multiple interacting agents in a centralised manner whilst keeping their execution decentralised. When the a…
q-bio.NC2016
Classifying HCP Task-fMRI Networks Using Heat Kernels
Ai Wern Chung, Emanuele Pesce, Ricardo Pio Monti +1
Network theory provides a principled abstraction of the human brain: reducing a complex system into a simpler representation from which to investigate brain organisation. Recent ad…