Xuesong Wang | DeepAI

AI Chat

Featured Co-authors

Yu Zhang
406 publications
Jingdong Wang
123 publications
Wei Jiang
113 publications
Yu Li
112 publications
Lina Yao
99 publications
Simon S. Du
95 publications
Sen Wang
88 publications
Richard E. Turner
75 publications
Hong Wang
70 publications
Wei Dai
62 publications
Xianzhi Wang
35 publications

∙ 06/12/2023

Evolving Testing Scenario Generation Method and Intelligence Evaluation Framework for Automated Vehicles

Interaction between the background vehicles (BVs) and automated vehicles...

0 Yining Ma, et al. ∙

∙ 09/01/2022

The Neural Process Family: Survey, Applications and Perspectives

The standard approaches to neural network implementation yield powerful ...

8 Saurav Jha, et al. ∙

∙ 08/02/2022

Automatic Classification of Bug Reports Based on Multiple Text Information and Reports' Intention

With the rapid growth of software scale and complexity, a large number o...

0 Fanqi Meng, et al. ∙

∙ 05/26/2022

Orthogonal Stochastic Configuration Networks with Adaptive Construction Parameter for Data Analytics

As a randomized learner model, SCNs are remarkable that the random weigh...

0 Wei Dai, et al. ∙

∙ 03/26/2022

Contrastive Graph Learning for Population-based fMRI Classification

Contrastive self-supervised learning has recently benefited fMRI classif...

0 Xuesong Wang, et al. ∙

∙ 02/04/2022

TransFollower: Long-Sequence Car-Following Trajectory Prediction through Transformer

Car-following refers to a control process in which the following vehicle...

0 Meixin Zhu, et al. ∙

∙ 12/05/2021

Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration

Muilti-modality data are ubiquitous in biology, especially that we have ...

0 Xuesong Wang, et al. ∙

∙ 09/02/2021

Global Convolutional Neural Processes

The ability to deal with uncertainty in machine learning models has beco...

42 Xuesong Wang, et al. ∙

∙ 01/29/2019

Safe, Efficient, and Comfortable Velocity Control based on Reinforcement Learning for Autonomous Driving

A model used for velocity control during car following was proposed base...

0 Meixin Zhu, et al. ∙

∙ 01/03/2019

Human-Like Autonomous Car-Following Model with Deep Reinforcement Learning

This study proposes a framework for human-like autonomous car-following ...

0 Meixin Zhu, et al. ∙

∙ 11/11/2018

Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study

Five car-following models were calibrated, validated and cross-compared....

8 Meixin Zhu, et al. ∙

∙ 05/22/2018

Modeling the Safety Effect of Access and Signal Density on Suburban Arterials: Using Macro Level Analysis Method

With rapidly increasing of the land development density along suburban a...

0 Jinghui Yuan, et al. ∙

∙ 05/20/2018

Utilizing Bluetooth and Adaptive Signal Control Data for Urban Arterials Safety Analysis

Real-time safety analysis has become a hot research topic as it can more...

0 Jinghui Yuan, et al. ∙

∙ 05/20/2018

Real-Time Crash Risk Analysis of Urban Arterials Incorporating Bluetooth, Weather, and Adaptive Signal Control Data

Real-time safety analysis has become a hot research topic as it can reve...

0 Jinghui Yuan, et al. ∙

∙ 05/16/2018

Modelling of crash types at signalized intersections based on random effect model

Approach-level models were developed to accommodate the diversity of app...

0 Xuesong Wang, et al. ∙

∙ 05/16/2018

Investigating Safety Impacts of Roadway Network Features of Suburban Arterials in Shanghai, China

With the rapid changes in land use development along suburban arterials ...

0 Xuesong Wang, et al. ∙

∙ 05/16/2018

Investigating the safety impacts of the roadway network features of suburban arterials in shanghai

With the rapid changes in land use development along suburban arterials ...

0 Xuesong Wang, et al. ∙

∙ 08/02/2017

Practically efficient methods for performing bit-reversed permutation in C++11 on the x86-64 architecture

The bit-reversed permutation is a famous task in signal processing and i...

0 Christian Knauth, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world