108 citations · 330 across the 34 of their papers we have counts for
12 papers · 1 filter
Unsupervised Multimodal Image Registration with Adaptative Gradient Guidance
Zhe Xu, Jiangpeng Yan, Jie Luo +2
Multimodal image registration (MIR) is a fundamental procedure in many image-guided therapies. Recently, unsupervised learning-based methods have demonstrated promising performance…
Unimodal Cyclic Regularization for Training Multimodal Image Registration Networks
Zhe Xu, Jiangpeng Yan, Jie Luo +3
The loss function of an unsupervised multimodal image registration framework has two terms, i.e., a metric for similarity measure and regularization. In the deep learning era, rese…
Real-time and Large-scale Fleet Allocation of Autonomous Taxis: A Case Study in New York Manhattan Island
Yue Yang, Wencang Bao, Mohsen Ramezani +1
Nowadays, autonomous taxis become a highly promising transportation mode, which helps relieve traffic congestion and avoid road accidents. However, it hinders the wide implementati…
F3RNet: Full-Resolution Residual Registration Network for Deformable Image Registration
Zhe Xu, Jie Luo, Jiangpeng Yan +2
Deformable image registration (DIR) is essential for many image-guided therapies. Recently, deep learning approaches have gained substantial popularity and success in DIR. Most dee…
Adversarial Uni- and Multi-modal Stream Networks for Multimodal Image Registration
Zhe Xu, Jie Luo, Jiangpeng Yan +4
Deformable image registration between Computed Tomography (CT) images and Magnetic Resonance (MR) imaging is essential for many image-guided therapies. In this paper, we propose a…
Reward Machines for Cooperative Multi-Agent Reinforcement Learning
Cyrus Neary, Zhe Xu, Bo Wu +1
In cooperative multi-agent reinforcement learning, a collection of agents learns to interact in a shared environment to achieve a common goal. We propose the use of reward machines…
Active Finite Reward Automaton Inference and Reinforcement Learning Using Queries and Counterexamples
Zhe Xu, Bo Wu, Aditya Ojha +2
Despite the fact that deep reinforcement learning (RL) has surpassed human-level performances in various tasks, it still has several fundamental challenges. First, most RL methods…
Distributed Policy Synthesis of Multi-Agent Systems With Graph Temporal Logic Specifications
Murat Cubuktepe, Zhe Xu, Ufuk Topcu
We study the distributed synthesis of policies for multi-agent systems to perform \emph{spatial-temporal} tasks. We formalize the synthesis problem as a \emph{factored} Markov deci…
Robust Inference and Verification of Temporal Logic Classifier-in-the-loop Systems
Zhe Xu
Autonomous systems embedded with machine learning modules often rely on deep neural networks for classifying different objects of interest in the environment or different actions o…
Policy Synthesis for Factored MDPs with Graph Temporal Logic Specifications
Murat Cubuktepe, Zhe Xu, Ufuk Topcu
We study the synthesis of policies for multi-agent systems to implement spatial-temporal tasks. We formalize the problem as a factored Markov decision process subject to so-called…
Policy Synthesis for Switched Linear Systems with Markov Decision Process Switching
Bo Wu, Murat Cubuktepe, Franck Djeumou +2
We study the synthesis of mode switching protocols for a class of discrete-time switched linear systems in which the mode jumps are governed by Markov decision processes (MDPs). We…
Active Task-Inference-Guided Deep Inverse Reinforcement Learning
Farzan Memarian, Zhe Xu, Bo Wu +2
We consider the problem of reward learning for temporally extended tasks. For reward learning, inverse reinforcement learning (IRL) is a widely used paradigm. Given a Markov decisi…