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Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Learning Augmented Optimization: Faster, Better and Guaranteed
Presented on November 20, 2019 at 12:15 p.m. in the Marcus Nanotechnology Building, Room 1116.Zhangyang (Atlas) Wang is an Assistant Professor of Computer Science and Engineering at Texas A&M University. Dr.
Wang, Zhangyang
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Abstract We present a comprehensive investigation into the learning capabilities of a simple d-level system (qudit). Our study is specialized for classification tasks using real-world databases, specifically the Iris, breast cancer, and MNIST datasets.
Sebastián Roca-Jerat +2 more
openaire +7 more sources
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Multi-view positive and unlabeled learning [PDF]
Learning with Positive and Unlabeled instances (PU learning) arises widely in information retrieval applications. To address the unavailability issue of negative instances, most existing PU learning approaches require to either identify a reliable set of
Tsang, IW +7 more
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FloBlocks: an affordable and extensible tool for tangible block programming in education
High costs often restrict access to programming education, especially in underserved communities. To address this, we introduce FloBlocks, a novel, low-cost educational tool that integrates tangible flowchart programming with computer vision.
Devansh Rathor +4 more
doaj +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Heterophily-informed Message Passing
Publisher Copyright: © 2025, Transactions on Machine Learning Research. All rights reserved.Graph neural networks (GNNs) are known to be vulnerable to oversmoothing due to their implicit homophily assumption.
Solin, Arno, Garg, Vikas, Wang, Haishan
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Traditionally, condition monitoring of wind turbines has been performed manually by certified rope teams. This method of inspection can be dangerous for the personnel involved, and the resulting downtime can be expensive.
Zachary Ward +5 more
doaj +1 more source
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios +5 more
wiley +1 more source

