Search Results for author: Zirui Li

Found 24 papers, 9 papers with code

RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Training

no code implementations27 Nov 2023 Hanrui Wang, Yilian Liu, Pengyu Liu, Jiaqi Gu, Zirui Li, Zhiding Liang, Jinglei Cheng, Yongshan Ding, Xuehai Qian, Yiyu Shi, David Z. Pan, Frederic T. Chong, Song Han

Arbitrary state preparation algorithms can be broadly categorized into arithmetic decomposition (AD) and variational quantum state preparation (VQSP).

Leveraging Multi-stream Information Fusion for Trajectory Prediction in Low-illumination Scenarios: A Multi-channel Graph Convolutional Approach

1 code implementation18 Nov 2022 Hailong Gong, Zirui Li, Chao Lu, Guodong Du, Jianwei Gong

The optical flow channel is applied to capture the pattern of relative motion between adjacent camera frames and modelled by Spatial-Temporal Graph Convolutional Network (ST-GCN).

Autonomous Vehicles Optical Flow Estimation +1

QuEst: Graph Transformer for Quantum Circuit Reliability Estimation

1 code implementation30 Oct 2022 Hanrui Wang, Pengyu Liu, Jinglei Cheng, Zhiding Liang, Jiaqi Gu, Zirui Li, Yongshan Ding, Weiwen Jiang, Yiyu Shi, Xuehai Qian, David Z. Pan, Frederic T. Chong, Song Han

Specifically, the TorchQuantum library also supports using data-driven ML models to solve problems in quantum system research, such as predicting the impact of quantum noise on circuit fidelity and improving the quantum circuit compilation efficiency.

Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discovery

no code implementations24 Jul 2022 Xianqi He, Lin Yang, Chao Lu, Zirui Li, Jianwei Gong

But in uncertain environments, they are not reliable, so learning-based methods are proposed, especially reinforcement learning (RL) methods.

Autonomous Driving Decision Making +3

QOC: Quantum On-Chip Training with Parameter Shift and Gradient Pruning

1 code implementation26 Feb 2022 Hanrui Wang, Zirui Li, Jiaqi Gu, Yongshan Ding, David Z. Pan, Song Han

Nevertheless, we find that due to the significant quantum errors (noises) on real machines, gradients obtained from naive parameter shift have low fidelity and thus degrading the training accuracy.

Image Classification

A Comparative Study of Deep Reinforcement Learning-based Transferable Energy Management Strategies for Hybrid Electric Vehicles

1 code implementation22 Feb 2022 Jingyi Xu, Zirui Li, Li Gao, Junyi Ma, Qi Liu, Yanan Zhao

Different exploration methods of DRL, including adding action space noise and parameter space noise, are compared against each other in the transfer learning process in this work.

energy management Management +3

QuantumNAT: Quantum Noise-Aware Training with Noise Injection, Quantization and Normalization

2 code implementations21 Oct 2021 Hanrui Wang, Jiaqi Gu, Yongshan Ding, Zirui Li, Frederic T. Chong, David Z. Pan, Song Han

Furthermore, to improve the robustness against noise, we propose noise injection to the training process by inserting quantum error gates to PQC according to realistic noise models of quantum hardware.

Denoising Quantization

Towards Efficient On-Chip Training of Quantum Neural Networks

no code implementations29 Sep 2021 Hanrui Wang, Zirui Li, Jiaqi Gu, Yongshan Ding, David Z. Pan, Song Han

The results demonstrate that our on-chip training achieves over 90% and 60% accuracy for 2-class and 4-class image classification tasks.

Image Classification

Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection

no code implementations8 Sep 2021 Shulai Zhang, Zirui Li, Quan Chen, Wenli Zheng, Jingwen Leng, Minyi Guo

Federated learning (FL) is a distributed machine learning paradigm that allows clients to collaboratively train a model over their own local data.

Federated Learning

Orientation-Aware Planning for Parallel Task Execution of Omni-Directional Mobile Robot

no code implementations2 Aug 2021 Cheng Gong, Zirui Li, Xingyu Zhou, Jiachen Li, Jianwei Gong, Junhui Zhou

Omni-directional mobile robot (OMR) systems have been very popular in academia and industry for their superb maneuverability and flexibility.

QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits

2 code implementations22 Jul 2021 Hanrui Wang, Yongshan Ding, Jiaqi Gu, Zirui Li, Yujun Lin, David Z. Pan, Frederic T. Chong, Song Han

Extensively evaluated with 12 QML and VQE benchmarks on 14 quantum computers, QuantumNAS significantly outperforms baselines.

Energy Management Strategy for Unmanned Tracked Vehicles Based on Local Speed Planning

no code implementations5 Jul 2021 Tianxing Sun, Shaohang Xu, Zirui Li, Yingqi Tan, Huiyan Chen

Finally, based on the prediction results, the model predictive control algorithm is used to realize the real-time optimization of energy management.

energy management Management

Decision-Making Technology for Autonomous Vehicles Learning-Based Methods, Applications and Future Outlook

no code implementations2 Jul 2021 Qi Liu, Xueyuan Li, Shihua Yuan, Zirui Li

Autonomous vehicles have a great potential in the application of both civil and military fields, and have become the focus of research with the rapid development of science and economy.

Autonomous Vehicles Decision Making

Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlooks

no code implementations24 Jun 2021 Lianzhen Wei, Zirui Li, Jianwei Gong, Cheng Gong, Jiachen Li

Due to the complex and dynamic character of intersection scenarios, the autonomous driving strategy at intersections has been a difficult problem and a hot point in the research of intelligent transportation systems in recent years.

Autonomous Driving

High-precision target positioning system for unmanned vehicles based on binocular vision

no code implementations17 Sep 2020 Xianqi He, Zirui Li, Xufeng Yin, Jianwei Gong, Cheng Gong

In order to verify the effect of the system, this paper collects the accuracy and calculation time of the output results of the cylinder in different poses.

Pose Estimation Stereo Matching

Stochastic Graph Recurrent Neural Network

no code implementations1 Sep 2020 Tijin Yan, Hongwei Zhang, Zirui Li, Yuanqing Xia

In addition, to alleviate KL-vanishing problem in SGRNN, a simple and interpretable structure is proposed based on the lower bound of KL-divergence.

Representation Learning Variational Inference

Driver Behavior Modelling at the Urban Intersection via Canonical Correlation Analysis

no code implementations11 Jul 2020 Zirui Li, Chao Lu, Cheng Gong, Jinghang Li, Lianzhen Wei

Accurately modelling the driver behavior at the intersection is essential for intelligent transportation systems (ITS).

feature selection regression

A Survey on Sensor Technologies for Unmanned Ground Vehicles

no code implementations4 Jul 2020 Qi Liu, Shihua Yuan, Zirui Li

Unmanned ground vehicles have a huge development potential in both civilian and military fields, and have become the focus of research in various countries.

From perception to control: an autonomous driving system for a formula student driverless car

1 code implementation31 Aug 2019 Tairan Chen, Zirui Li, Yiting He, Zewen Xu, Zhe Yan, Huiqian Li

This paper introduces the autonomous system of the "Smart Shark II" which won the Formula Student Autonomous China (FSAC) Competition in 2018.

Autonomous Driving

Choosing Transfer Languages for Cross-Lingual Learning

1 code implementation ACL 2019 Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, Zirui Li, Yuyan Zhang, Mengzhou Xia, Shruti Rijhwani, Junxian He, Zhisong Zhang, Xuezhe Ma, Antonios Anastasopoulos, Patrick Littell, Graham Neubig

Cross-lingual transfer, where a high-resource transfer language is used to improve the accuracy of a low-resource task language, is now an invaluable tool for improving performance of natural language processing (NLP) on low-resource languages.

Cross-Lingual Transfer

Towards a General-Purpose Linguistic Annotation Backend

no code implementations13 Dec 2018 Graham Neubig, Patrick Littell, Chian-Yu Chen, Jean Lee, Zirui Li, Yu-Hsiang Lin, Yuyan Zhang

In this extended abstract, we describe the beginnings of a new project that will attempt to ease this language documentation process through the use of natural language processing (NLP) technology.


Learning and Generalizing Motion Primitives from Driving Data for Path-Tracking Applications

no code implementations2 Jun 2018 Boyang Wang, Zirui Li, Jianwei Gong, Yidi Liu, Huiyan Chen, Chao Lu

Therefore, the goal of this paper is to generate the prediction results of lateral commands with confidence regions according to the reference based on the learned motion primitives.


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