Search Results for author: Peng Xie

Found 13 papers, 2 papers with code

Hybrid Polynomial Zonotopes: A Set Representation for Reachability Analysis in Hybrid Nonaffine Systems

no code implementations16 Jun 2025 Peng Xie, Zhen Zhang, Amr Alanwar

Reachability analysis for hybrid nonaffine systems remains computationally challenging, as existing set representations--including constrained, polynomial, and hybrid zonotopes--either lose tightness under high-order nonaffine maps or suffer exponential blow-up after discrete jumps.

Computational Efficiency

Data-Driven Reachability Analysis for Piecewise Affine Systems

2 code implementations6 Apr 2025 Peng Xie, Johannes Betz, Davide M. Raimondo, Amr Alanwar

Hybrid systems play a crucial role in modeling real-world applications where discrete and continuous dynamics interact, including autonomous vehicles, power systems, and traffic networks.

Autonomous Vehicles

Chain of Attack: On the Robustness of Vision-Language Models Against Transfer-Based Adversarial Attacks

no code implementations CVPR 2025 Peng Xie, Yequan Bie, Jianda Mao, Yangqiu Song, Yang Wang, Hao Chen, Kani Chen

Pre-trained vision-language models (VLMs) have showcased remarkable performance in image and natural language understanding, such as image captioning and response generation.

Image Captioning Natural Language Understanding +1

The Mitochondrial Genome of Cathaya argyrophylla Reaches 18.99 Mb: Analysis of Super-Large Mitochondrial Genomes in Pinaceae

no code implementations9 Oct 2024 Kerui Huang, Wenbo Xu, Haoliang Hu, XiaoLong Jiang, Lei Sun, Wenyan Zhao, Binbin Long, Shaogang Fan, Zhibo Zhou, Ping Mo, Xiaocheng Jiang, Jianhong Tian, Aihua Deng, Peng Xie, Yun Wang

In this study, we sequenced and analyzed the mitochondrial genome of Cathaya argyrophylla, an endangered and endemic Pinaceae species, uncovering a genome size of 18. 99 Mb, meaning the largest mitochondrial genome reported to date.

UMOD: A Novel and Effective Urban Metro Origin-Destination Flow Prediction Method

no code implementations8 Sep 2024 Peng Xie, Minbo Ma, Bin Wang, Junbo Zhang, Tianrui Li

Accurate prediction of metro Origin-Destination (OD) flow is essential for the development of intelligent transportation systems and effective urban traffic management.

Prediction Relation

AdaMR: Adaptable Molecular Representation for Unified Pre-training Strategy

no code implementations28 Dec 2023 Yan Ding, Hao Cheng, Ziliang Ye, Ruyi Feng, Wei Tian, Peng Xie, Juan Zhang, Zhongze Gu

We fine-tuned our proposed pre-trained model on six molecular property prediction tasks (MoleculeNet datasets) and two generative tasks (ZINC250K datasets), achieving state-of-the-art (SOTA) results on five out of eight tasks.

Attribute Molecular Property Prediction +2

Key Gene Mining in Transcriptional Regulation for Specific Biological Processes with Small Sample Sizes Using Multi-network pipeline Transformer

no code implementations7 Aug 2023 Kerui Huang, Jianhong Tian, Lei Sun, Li Zeng, Peng Xie, Aihua Deng, Ping Mo, Zhibo Zhou, Ming Jiang, Yun Wang, Xiaocheng Jiang

Gene mining is an important topic in the field of life sciences, but traditional machine learning methods cannot consider the regulatory relationships between genes.

Data Augmentation

Spatio-Temporal Dynamic Graph Relation Learning for Urban Metro Flow Prediction

no code implementations6 Apr 2022 Peng Xie, Minbo Ma, Tianrui Li, Shenggong Ji, Shengdong Du, Zeng Yu, Junbo Zhang

Second, we employ a dynamic graph relationship learning module to learn dynamic spatial relationships between metro stations without a predefined graph adjacency matrix.

Management Prediction +3

HiSTGNN: Hierarchical Spatio-temporal Graph Neural Networks for Weather Forecasting

no code implementations22 Jan 2022 Minbo Ma, Peng Xie, Fei Teng, Tianrui Li, Bin Wang, Shenggong Ji, Junbo Zhang

In this paper, we propose a novel Hierarchical Spatio-Temporal Graph Neural Network (HiSTGNN) to model cross-regional spatio-temporal correlations among meteorological variables in multiple stations.

Graph Learning Graph Neural Network +4

Exploring Multi-dimensional Data via Subset Embedding

no code implementations24 Apr 2021 Peng Xie, Wenyuan Tao, Jie Li, Wentao Huang, Siming Chen

The core of the approach is a subset embedding network (SEN) that represents a group of subsets as uniformly-formatted embeddings.

Quality Control of Neuron Reconstruction Based on Deep Learning

no code implementations19 Mar 2020 Donghuan Lu, Sujun Zhao, Peng Xie, Kai Ma, Li-Juan Liu, Yefeng Zheng

To ensure the quality of reconstructed neurons and provide guidance for annotators to improve their efficiency, we propose a deep learning based quality control method for neuron reconstruction in this paper.

Binary Classification Deep Learning

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