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Showing 41527 results for "machine learning" in Engineering
Engineering Preprint PDF DOI

Physics-informed, Generative Adversarial Design of Funicular Shells

Ruben Lourenco, Iciar Alfaro, Beatriz Moya, Elias Cueto · 2026

Shell structures are pivotal in the fields of architecture and engineering, due to their aesthetic appeal and structural efficiency. Recently, 3D concrete printing has reignited the interest in these …

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Engineering Preprint PDF DOI

CVaR-Guided Decision-Focused Learning and Risk-Triggered Re-Optimization for Two-Stage Robust Microgrid Operation

Tingwei Cao, Yan Xu · 2026

Microgrid operation is highly vulnerable to short-term load uncertainty, while conventional predict-then-optimize pipelines cannot fully align probabilistic forecasting quality with downstream robust …

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Engineering Preprint PDF DOI

Human Cognition in Machines: A Unified Perspective of World Models

Timothy Rupprecht, Pu Zhao, Amir Taherin, Arash Akbari, Arman Akbari, Yumei He, Sean Duffy, Juyi Lin, Yixiao Chen, Rahul Chowdhury, Enfu Nan, Yixin Shen, Yifan Cao, Haochen Zeng, Weiwei Chen, Geng Yuan, Jennifer Dy, Sarah Ostadabbas, Silvia Zhang, David Kaeli, Edmund Yeh, Yanzhi Wang · 2026

This comprehensive report distinguishes prior works by the cognitive functions they innovate. Many works claim an almost "human-like" cognitive capability in their world models. To evaluate these clai…

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Engineering Preprint PDF DOI

Safe Deep Reinforcement Learning for Building Heating Control and Demand-side Flexibility

Colin Juni, Mina Montazeri, Yi Guo, Federica Bellizio, Giovanni Sansavini, Philipp Heer · 2026

Buildings account for approximately 40% of global energy consumption, and with the growing share of intermittent renewable energy sources, enabling demand-side flexibility, particularly in heating, ve…

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Engineering Preprint PDF DOI

A Reconfigurable Pneumatic Joint Enabling Localized Selective Stiffening and Shape Locking in Vine-Inspired Robots

Ayodele James Oyejide, Ustaz A. Yaqub, Samir Erturk, Eray A. Baran, Fabio Stroppa · 2026

Vine-inspired robots achieve large workspace coverage through tip eversion, enabling safe navigation in confined and cluttered environments. However, their deployment in free space is fundamentally li…

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Engineering Preprint PDF DOI

Limits of Lamarckian Evolution Under Pressure of Morphological Novelty

Jed R Muff, Karine Miras, A.E. Eiben · 2026

Lamarckian inheritance has been shown to be a powerful accelerator in systems where the joint evolution of robot morphologies and controllers is enhanced with individual learning. Its defining advanta…

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Engineering Preprint PDF DOI

From Seeing to Simulating: Generative High-Fidelity Simulation with Digital Cousins for Generalizable Robot Learning and Evaluation

Jasper Lu, Zhenhao Shen, Yuanfei Wang, Shugao Liu, Shengqiang Xu, Shawn Xie, Jingkai Xu, Feng Jiang, Jade Yang, Chen Xie, Ruihai Wu · 2026

Learning robust robot policies in real-world environments requires diverse data augmentation, yet scaling real-world data collection is costly due to the need for acquiring physical assets and reconfi…

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Engineering Preprint PDF DOI

Fuzzy Logic Theory-based Adaptive Reward Shaping for Robust Reinforcement Learning (FARS)

Hurkan Sahin, Van Huyen Dang, Erdi Sayar, Alper Yegenoglu, Erdal Kayacan · 2026

Reinforcement learning (RL) often struggles in real-world tasks with high-dimensional state spaces and long horizons, where sparse or fixed rewards severely slow down exploration and cause agents to g…

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Engineering Preprint PDF DOI

Integrating AI and Simulation for Teaching Power System Dynamics: An Interactive Framework for Engineering Education

Osasumwen Cedric Ogiesoba-Eguakun, Phani Kumar Inkollu, Rupesh Sah, Zia Rashid, Douglas Jussaume, Suman Rath · 2026

Artificial Intelligence (AI), especially cloud platforms and large language models (LLMs), is changing how engineering is taught by making learning more interactive and flexible. However, in electrica…

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Engineering Preprint PDF DOI

Discovery of unobservable parameters via physical embedding

Le Cheng, Xiaoran Liu, Lingjin Kong, Haitao Zhao, Jun Xiong, Fanglin Gu, Xiaoying Zhang, Baoquan Ren, Jibo Wei, Hao Yin · 2026

Recovering a source signal from indirect measurements often requires estimating latent parameters, such as wireless channel states or MRI coil sensitivities, that cannot be directly observed. Here, we…

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Engineering Preprint PDF DOI

Perron-Frobenius Contractive Operator Matching for Data-Driven Reachable Fault Identification and Recovery

Joshua D. Ibrahim, Mahdi Taheri, Soon-Jo Chung, Fred Y. Hadaegh · 2026

This paper focuses on data-driven fault detection, identification, and recovery (FDIR) for nonlinear control-affine systems under actuator faults. We create a unified framework in the space of probabi…

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Engineering Preprint PDF DOI

RelativeFlow: Taming Medical Image Denoising Learning with Noisy Reference

Yuxin Liu, Yiqing Dong, Wenxue Yu, Zhan Wu, Rongjun Ge, Yang Chen, Yuting He · 2026

Medical image denoising (MID) lacks absolutely clean images for supervision, leading to a noisy reference problem that fundamentally limits denoising performance. Existing simulated-supervised discrim…

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Engineering Preprint PDF DOI

Abstract Sim2Real through Approximate Information States

Yunfu Deng, Yuhao Li, Josiah P. Hanna · 2026

In recent years, reinforcement learning (RL) has shown remarkable success in robotics when a fast and accurate simulator is available for a given task. When using RL and simulation, more simulator rea…

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Engineering Preprint PDF DOI

A Nonlinear Separation Principle via Contraction Theory: Applications to Neural Networks, Control, and Learning

Anand Gokhale, Anton V. Proskurnikov, Yu Kawano, Francesco Bullo · 2026

This paper establishes a nonlinear separation principle based on contraction theory and derives sharp stability conditions for recurrent neural networks (RNNs). First, we introduce a nonlinear separat…

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Engineering Preprint PDF DOI

A Hierarchical Spatiotemporal Action Tokenizer for In-Context Imitation Learning in Robotics

Fawad Javed Fateh, Ali Shah Ali, Murad Popattia, Usman Nizamani, Andrey Konin, M. Zeeshan Zia, Quoc-Huy Tran · 2026

We present a novel hierarchical spatiotemporal action tokenizer for in-context imitation learning. We first propose a hierarchical approach, which consists of two successive levels of vector quantizat…

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Engineering Preprint PDF DOI

Ternary Noise Modulation

Ata Bilgin, Erkin Yap{i}c{i}, Yusuf Islam Tek, Ertugrul Basar · 2026

By exploiting noise as an information-bearing resource, noise-driven communication offers a promising framework for low-complexity and secure wireless system design. In this letter, the scheme of tern…

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Engineering Preprint PDF DOI

DockAnywhere: Data-Efficient Visuomotor Policy Learning for Mobile Manipulation via Novel Demonstration Generation

Ziyu Shan, Yuheng Zhou, Gaoyuan Wu, Ziheng Ji, Zhenyu Wu, Ziwei Wang · 2026

Mobile manipulation is a fundamental capability that enables robots to interact in expansive environments such as homes and factories. Most existing approaches follow a two-stage paradigm, where the r…

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Engineering Preprint PDF DOI

Momentum-constrained Hybrid Heuristic Trajectory Optimization Framework with Residual-enhanced DRL for Visually Impaired Scenarios

Yuting Zeng, Zhiwen Zheng, Jingya Wang, You Zhou, JiaLing Xiao, Yongbin Yu, Manping Fan, Bo Gong, Liyong Ren · 2026

Safe and efficient assistive planning for visually impaired scenarios remains challenging, since existing methods struggle with multi-objective optimization, generalization, and interpretability. In r…

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Engineering Preprint PDF DOI

HRDexDB: A Large-Scale Dataset of Dexterous Human and Robotic Hand Grasps

Jongbin Lim, Taeyun Ha, Mingi Choi, Jisoo Kim, Byungjun Kim, Subin Jeon, Hanbyul Joo · 2026

We present HRDexDB, a large-scale, multi-modal dataset of high-fidelity dexterous grasping sequences featuring both human and diverse robotic hands. Unlike existing datasets, HRDexDB provides a compre…

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Engineering Preprint PDF DOI

4D Radar Gaussian Modeling and Scan Matching with RCS

Fernando Amodeo, Luis Merino, Fernando Caballero · 2026

4D millimeter-wave (mmWave) radars are increasingly used in robotics, as they offer robustness against adverse environmental conditions. Besides the usual XYZ position, they provide Doppler velocity m…

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