most citedGraph Curvature and the Robustness of Cancer Networks

13 citations · 26 across the 4 of their papers we have counts for

collaborators

5 papers

eess.SY2019

Maxwells Demon: Controlling Entropy via Discrete Ricci Flow Over Networks

Romeil Sandhu, Ji Liu

In this work, we propose to utilize discrete graph Ricci flow to alter network entropy through feedback control. Given such feedback input can reverse entropic changes, we adapt th…

cs.CV2019

An Interactive Control Approach to 3D Shape Reconstruction

Bipul Islam, Ji Liu, Anthony Yezzi +1

The ability to accurately reconstruct the 3D facets of a scene is one of the key problems in robotic vision. However, even with recent advances with machine learning, there is no h…

cs.LG20192 cited

A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning

Yixuan Lin, Kaiqing Zhang, Zhuoran Yang +4

This paper considers a distributed reinforcement learning problem in which a network of multiple agents aim to cooperatively maximize the globally averaged return through communica…

q-fin.RM201511 cited

Market Fragility, Systemic Risk, and Ricci Curvature

Romeil Sandhu, Tryphon Georgiou, Allen Tannenbaum

Measuring systemic risk or fragility of financial systems is a ubiquitous task of fundamental importance in analyzing market efficiency, portfolio allocation, and containment of fi…

q-bio.MN201513 cited

Graph Curvature and the Robustness of Cancer Networks

Allen Tannenbaum, Chris Sander, Liangjia Zhu +5

The importance of studying properties of networks is manifest in diverse fields ranging from biology, engineering, physics, chemistry, neuroscience, and medicine. The functionality…