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Showing 41082 results for "deep learning" in Engineering
Engineering Preprint PDF DOI

Adaptive Spatial-Temporal Graph Learning-Enabled Short-Term Voltage Stability Assessment against Time-Varying Topological Conditions

Chao Deng, Lipeng Zhu, Chang Liu, Hefeng Zhai, Baoye Tian, Zexiang Zhu, Jiayong Li, Cong Zhang · 2026

The emerging deep learning (DL) technology has recently exhibited great potential in data-driven short-term voltage stability (SVS) assessment of complex power grids. However, without sufficient atten…

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Engineering Preprint PDF DOI

Cooperative Informative Sensing for Monitoring Dynamic Indoor Environments via Multi-Agent Reinforcement Learning

Kanghoon Lee, Matthew M. Sato, Jinnyeong Yang, Seungro Lee, Sujin Lee, Jiachen Li, Kuk-Jin Yoon, Jinkyoo Park, Kincho H. Law, Yoonjin Yoon · 2026

Monitoring human activity in indoor environments is important for applications such as facility management, safety assessment, and space utilization analysis. While mobile robot teams offer the potent…

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Engineering Preprint PDF DOI

UAV Trajectory and Bandwidth Allocation for Efficient Data Collection in Low-Altitude Intelligent IoT: A Hierarchical DRL Approach

Zhenjia Xu, Xiaoling Zhang, Nan Qi, Xiaojie Li, Luliang Jia · 2026

Under the 6G wireless network evolution, the low-altitude Internet of Things (IoT), supported by unmanned aerial vehicles (UAVs) with Integrated Sensing and Communication (ISAC) capabilities, provides…

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Engineering Preprint PDF DOI

In-context modeling as a retrain-free paradigm for foundation models in computational science

Lingfeng Li, Zhuoyuan Li, Shun Li, Kaixin Zhan, Huajian Gao, Changqing Chen, Liu Yang · 2026

Building models that generalize across physical systems without retraining remains a central challenge in computational science. Here we introduce In-Context Modeling (ICM), a retrain-free paradigm th…

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Engineering Preprint PDF DOI

Learning the Weather-Grid Nexus via Weather-to-Voltage (W2V) Predictive Modeling

Sol Lim, Min-Seung Ko, Farnaz Safdarian, Hao Zhu · 2026

This paper proposes a weather-to-voltage (W2V) predictive modeling framework to learn the underlying weather-grid nexus. Unlike existing approaches on weather-informed grid operations, our proposed W2…

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Engineering Preprint PDF DOI

Learning to Trust AI and Data-driven models in Data Assimilation through a Multifidelity Ensemble Gaussian Mixture Filter Framework

Andrey A. Popov · 2026

AI and data-driven models have large potential for data assimilation applications by creating fast and accurate forecasts. Their tendency to produce spurious inaccurate, nonphysical results -- halluci…

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Engineering Preprint PDF DOI

Vision-Language-Action in Robotics: A Survey of Datasets, Benchmarks, and Data Engines

Ziyao Wang, Bingying Wang, Hanrong Zhang, Tingting Du, Tianyang Chen, Guoheng Sun, Yexiao He, Zheyu Shen, Wanghao Ye, Ang Li · 2026

Despite remarkable progress in Vision--Language--Action (VLA) models, a central bottleneck remains underexamined: the data infrastructure that underlies embodied learning. In this survey, we argue tha…

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Engineering Preprint PDF DOI

Learning from the Best: Smoothness-Driven Metrics for Data Quality in Imitation Learning

Soham Kulkarni, Raayan Dhar, Yuchen Cui · 2026

In behavioral cloning (BC), policy performance is fundamentally limited by demonstration data quality. Real-world datasets contain trajectories of varying quality due to operator skill differences, te…

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Engineering Preprint PDF DOI

GCImOpt: Learning efficient goal-conditioned policies by imitating optimal trajectories

Jon Goikoetxea, Jesus F. Palacian · 2026

Imitation learning is a well-established approach for machine-learning-based control. However, its applicability depends on having access to demonstrations, which are often expensive to collect and/or…

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Engineering Preprint PDF DOI

ATRS: Adaptive Trajectory Re-splitting via a Shared Neural Policy for Parallel Optimization

Jiajun Yu, Guodong Liu, Li Wang, Pengxiang Zhou, Wentao Liu, Yin He, Chao Xu, Fei Gao, Yanjun Cao · 2026

Parallel trajectory optimization via the Alternating Direction Method of Multipliers (ADMM) has emerged as a scalable approach to long-horizon motion planning. However, existing frameworks typically d…

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Engineering Preprint PDF DOI

CT-Guided Spatially-varying Regularization for Voxel-Wise Deformable Whole-Body PET Registration

Xiangcen Wu, Ruohua Chen, Sichun Li, Qianye Yang, Sheng Liu, Jianjun Liu, Zhaoheng Xie · 2026

Whole-body Positron Emission Tomography (PET) registration is essential for multi-parametric tumor characterization and assessment of metastatic disease progression. In deep learning-based deformable …

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Engineering Preprint PDF DOI

Mobility Aware Power Control for VCSEL Based Indoor OWC

Walter Zibusiso Ncube, Ahmad Adnan Qidan, Taisir El-Gorashi, Jaafar M. H. Elmirghani · 2026

Optical wireless communication (OWC) is a promising technology for supporting data intensive services in indoor environments due to its large unregulated spectrum, high spatial reuse, and potential fo…

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Engineering Preprint PDF DOI

GazeVLA: Learning Human Intention for Robotic Manipulation

Chengyang Li, Kaiyi Xiong, Yuan Xu, Lei Qian, Yizhou Wang, Wentao Zhu · 2026

Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstrations. Although recent works have explored lever…

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Engineering Preprint PDF DOI

Useful nonrobust features are ubiquitous in biomedical images

Coenraad Mouton, Randle Rabe, Niklas C. Koser, Nicolai Krekiehn, Christopher Hansen, Jan-Bernd Hovener, Claus-C. Gluer · 2026

We study whether deep networks for medical imaging learn useful nonrobust features - predictive input patterns that are not human interpretable and highly susceptible to small adversarial perturbation…

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Engineering Preprint PDF DOI

QDTraj: Exploration of Diverse Trajectory Primitives for Articulated Objects Robotic Manipulation

Mathilde Kappel, Mahdi Khoramshahi, Louis Annabi, Faiz Ben Amar, Stephane Doncieux · 2026

Thanks to the latest advances in learning and robotics, domestic robots are beginning to enter homes, aiming to execute household chores autonomously. However, robots still struggle to perform autonom…

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Engineering Preprint PDF DOI

Information-Theoretic Geometry Optimization and Physics-Aware Learning for Calibration-Free Magnetic Localization

Wenxuan Xie, Yuelin Zhang, Qingpeng Ding, Jianghua Chen, Jiewen Tan, Jiwei Shan, Shing Shin Cheng · 2026

Wireless localization of permanent magnets enables occlusion-free guidance for medical interventions, yet its practical accuracy is fundamentally limited by two coupled challenges: the poor observabil…

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Engineering Preprint PDF DOI

DM-ASR: Diarization-aware Multi-speaker ASR with Large Language Models

Li Li, Ming Cheng, Weixin Zhu, Yannan Wang, Juan Liu, Ming Li · 2026

Multi-speaker automatic speech recognition (ASR) aims to transcribe conversational speech involving multiple speakers, requiring the model to capture not only what was said, but also who said it and s…

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Engineering Preprint PDF DOI

Selective Depthwise Separable Convolution for Lightweight Joint Source-Channel Coding in Wireless Image Transmission

Ming Ye, Kui Cai, Cunhua Pan, Zhen Mei, Wanting Yang, Chunguo Li · 2026

Depthwise separable convolutional (DSConv) layers have been successfully applied to deep learning (DL)-based joint source-channel coding (JSCC) schemes to reduce computational complexity. However, a s…

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Engineering Preprint PDF DOI

Learning Control Policies to Provably Satisfy Hard Affine Constraints for Black-Box Hybrid Dynamical Systems

Aayushi Shrivastava, Kartik Nagpal, Sairam Jinkala, Jean-Baptiste Bouvier, Negar Mehr · 2026

Ensuring safety for black-box hybrid dynamical systems presents significant challenges due to their instantaneous state jumps and unknown explicit nonlinear dynamics. Existing solutions for strict saf…

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Engineering Preprint PDF DOI

Learning-augmented robotic automation for real-world manufacturing

Yunho Kim, Quan Nguyen, Taewhan Kim, Youngjin Heo, Joonho Lee · 2026

Industrial robots are widely used in manufacturing, yet most manipulation still depends on fixed waypoint scripts that are brittle to environmental changes. Learning-based control offers a more adapti…

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