40 citations · 76 across the 15 of their papers we have counts for
15 papers
A Multilayer Perceptron-based Fast Sunlight Assessment for the Conceptual Design of Residential Neighborhoods under Chinese Policy
Can Jiang, Xiong Liang, Yu-Cheng Zhou +6
In Chinese building codes, it is required that residential buildings receive a minimum number of hours of natural, direct sunlight on a specified winter day, which represents the w…
Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D
Bo Qiang, Yuxuan Song, Minkai Xu +5
Generating desirable molecular structures in 3D is a fundamental problem for drug discovery. Despite the considerable progress we have achieved, existing methods usually generate m…
Direct Heterogeneous Causal Learning for Resource Allocation Problems in Marketing
Hao Zhou, Shaoming Li, Guibin Jiang +2
Marketing is an important mechanism to increase user engagement and improve platform revenue, and heterogeneous causal learning can help develop more effective strategies. Most dec…
Backward Euler method for stochastic differential equations with non-Lipschitz coefficients
Hao Zhou, Yaozhong Hu, Yanghui Liu
We study the traditional backward Euler method for -dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter whose drift…
Optimal Bailouts and Strategic Debt Forgiveness in Financial Networks
Panagiotis Kanellopoulos, Maria Kyropoulou, Hao Zhou
A financial system is represented by a network, where nodes correspond to banks, and directed labeled edges correspond to debt contracts between banks. Once a payment schedule has…
Impact of Acceleration/deceleration Limits on the String Stability of Adaptive Cruise Control
Hao Zhou, Anye Zhou, Tienan Li +3
This paper demonstrates that the acceleration/deceleration limits in ACC systems can make a string stable ACC amplify the speed perturbation in natural driving. It is shown that th…
Fundamental Diagrams of Commercial Adaptive Cruise Control: Worldwide Experimental Evidence
Tienan Li, Danjue Chen, Hao Zhou +2
Experimental measurements on commercial adaptive cruise control (ACC) vehicles \RoundTwo{are} becoming increasingly available from around the world, providing an unprecedented oppo…
Rapid feasibility assessment of components formed through hot stamping: A deep learning approach
Hamid Reza Attar, Haosu Zhou, Alistair Foster +1
The novel non-isothermal Hot Forming and cold die Quenching (HFQ) process can enable the cost-effective production of complex shaped, high strength aluminium alloy panel components…
Which to Match? Selecting Consistent GT-Proposal Assignment for Pedestrian Detection
Yan Luo, Chongyang Zhang, Muming Zhao +2
Accurate pedestrian classification and localization have received considerable attention due to their wide applications such as security monitoring, autonomous driving, etc. Althou…
SuperMeshing: A New Deep Learning Architecture for Increasing the Mesh Density of Metal Forming Stress Field with Attention Mechanism and Perceptual Features
Qingfeng Xu, Zhenguo Nie, Handing Xu +2
In stress field analysis, the finite element analysis is a crucial approach, in which the mesh-density has a significant impact on the results. High mesh density usually contribute…
Accelerated computational micromechanics
Hao Zhou, Kaushik Bhattacharya
We present an approach to solving problems in micromechanics that is amenable to massively parallel calculations through the use of graphical processing units and other accelerator…
A study on using image based machine learning methods to develop the surrogate models of stamp forming simulations
Haosu Zhou, Qingfeng Xu, Nan Li
In the design optimization of metal forming, it is increasingly significant to use surrogate models to analyse the finite element analysis (FEA) simulations. However, traditional s…
Congested Urban Networks Tend to Be Insensitive to Signal Settings: Implications for Learning-Based Control
Jorge Laval, Hao Zhou
This paper highlights several properties of large urban networks that can have an impact on machine learning methods applied to traffic signal control. In particular, we show that…
Large-scale traffic signal control using machine learning: some traffic flow considerations
Jorge A. Laval, Hao Zhou
This paper uses supervised learning, random search and deep reinforcement learning (DRL) methods to control large signalized intersection networks. The traffic model is Cellular Au…
Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty
Hao Henry Zhou, Yunyang Xiong, Vikas Singh
We provide simple schemes to build Bayesian Neural Networks (BNNs), block by block, inspired by a recent idea of computation skeletons. We show how by adjusting the types of blocks…