680 citations · 2.2k across the 23 of their papers we have counts for
23 papers
Pattern Expansion of Spin Glasses
Mutian Shen, Zohar Nussinov, Yang-Yu Liu
We introduce a systematic method for expanding general spin-glass Hamiltonians in terms of Mattis interactions, providing a novel perspective for understanding the fundamental diff…
Doubly heterogeneous networks facilitate the emergence of collective cooperation
Yao Meng, Sean P. Cornelius, Yang-Yu Liu +1
There is growing recognition that the network structures arising from interactions between different entities in physical, social and biological systems fundamentally alter the evo…
Finding spin glass ground states through deep reinforcement learning
Changjun Fan, Mutian Shen, Zohar Nussinov +3
Spin glasses are disordered magnets with random interactions that are, generally, in conflict with each other. Finding the ground states of spin glasses is not only essential for t…
Optimal Vaccine Allocation for Pandemic Stabilization
Qianqian Ma, Yang-Yu Liu, Alex Olshevsky
How to strategically allocate the available vaccines is a crucial issue for pandemic control. In this work, we propose a mathematical framework for optimal stabilizing vaccine allo…
Controlling network dynamics
Aming Li, Yang-Yu Liu
Network science has experienced unprecedented rapid development in the past two decades. The network perspective has also been widely applied to explore various complex systems in…
Control energy scaling in temporal networks
Aming Li, Sean P. Cornelius, Yang-Yu Liu +2
In practical terms, controlling a network requires manipulating a large number of nodes with a comparatively small number of external inputs, a process that is facilitated by paths…
A Tensor-Based Framework for Studying Eigenvector Multicentrality in Multilayer Networks
Mincheng Wu, Shibo He, Yongtao Zhang +5
Centrality is widely recognized as one of the most critical measures to provide insight in the structure and function of complex networks. While various centrality measures have be…
Tailoring Artificial Neural Networks for Optimal Learning
Pau Vilimelis Aceituno, Yan Gang, Yang-Yu Liu
As one of the most important paradigms of recurrent neural networks, the echo state network (ESN) has been applied to a wide range of fields, from robotics to medicine, finance, an…
Bridges in Complex Networks
Ang-Kun Wu, Liang Tian, Yang-Yu Liu
A bridge in a graph is an edge whose removal disconnects the graph and increases the number of connected components. We calculate the fraction of bridges in a wide range of real-wo…
Sensitivity of Complex Networks
Marco Tulio Angulo, Gabor Lippner, Yang-Yu Liu +1
The sensitivity (i.e. dynamic response) of complex networked systems has not been well understood, making difficult to predict whether new macroscopic dynamic behavior will emerge…
Articulation Points in Complex Networks
Liang Tian, Amir Bashan, Da-Ning Shi +1
An articulation point in a network is a node whose removal disconnects the network. Those nodes play key roles in ensuring connectivity of many real-world networks, from infrastruc…
Covering Problems and Core Percolations on Hypergraphs
Bruno Coelho Coutinho, Hai-Jun Zhou, Yang-Yu Liu
Covering problems are classical computational problems concerning whether a certain combinatorial structure 'covers' another. For example, the minimum vertex covering problem aims…
Control principles of metabolic networks
Georg Basler, Zoran Nikoloski, Abdelhalim Larhlimi +2
Deciphering the control principles of metabolism and its interaction with other cellular functions is central to biomedicine and biotechnology. Yet, understanding the efficient con…
Control Principles of Complex Networks
Yang-Yu Liu, Albert-Laszló Barabási
A reflection of our ultimate understanding of a complex system is our ability to control its behavior. Typically, control has multiple prerequisites: It requires an accurate map of…
Fundamental limitations of network reconstruction
Marco Tulio Angulo, Jaime A. Moreno, Albert-László Barabási +1
Network reconstruction is the first step towards understanding, diagnosing and controlling the dynamics of complex networked systems. It allows us to infer properties of the intera…
Emergence of bimodality in controlling complex networks
Tao Jia, Yang-Yu Liu, Endre Csóka +3
Our ability to control complex systems is a fundamental challenge of contemporary science. Recently introduced tools to identify the driver nodes, nodes through which we can achiev…
Spectrum of Controlling and Observing Complex Networks
Gang Yan, Georgios Tsekenis, Baruch Barzel +3
Observing and controlling complex networks are of paramount interest for understanding complex physical, biological and technological systems. Recent studies have made important ad…
Stability of Degree Heterogeneous Ecological Networks
Gang Yan, Neo D. Martinez, Yang-Yu Liu
A classic measure of ecological stability describes the tendency of a community to return to equilibrium after small perturbation. While many advances show how the network structur…
Individual dynamics induces symmetry in network controllability
Chen Zhao, Wen-Xu Wang, Yang-Yu Liu +1
Controlling complex networked systems to a desired state is a key research goal in contemporary science. Despite recent advances in studying the impact of network topology on contr…
Inducing Effect on the Percolation Transition in Complex Networks
Jin-Hua Zhao, Hai-Jun Zhou, Yang-Yu Liu
Percolation theory concerns the emergence of connected clusters that percolate through a networked system. Previous studies ignored the effect that a node outside the percolating c…
Core percolation on complex networks
Yang-Yu Liu, Endre Csóka, Haijun Zhou +1
As a fundamental structural transition in complex networks, core percolation is related to a wide range of important problems. Yet, previous theoretical studies of core percolation…
Control centrality and hierarchical structure in complex networks
Yang-Yu Liu, Jean-Jacques Slotine, Albert-László Barabási
We introduce the concept of control centrality to quantify the ability of a single node to control a directed weighted network. We calculate the distribution of control centrality…
Effect of correlations on network controllability
Márton Pósfai, Yang-Yu Liu, Jean-Jacques Slotine +1
A dynamical system is controllable if by imposing appropriate external signals on a subset of its nodes, it can be driven from any initial state to any desired state in finite time…