GitHub

Strong Partitioning and a Machine Learning Approximation for Accelerating the Global Optimization of Nonconvex QCQPs

To cite the contents of this repository, please cite both the paper and the INFORMS Journal on Computing GitHub repo, using their respective DOIs.

Machine learning workflow enables faster, more reliable organic crystal structure prediction

Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...
VoxelMatters

Physics-based machine learning unlocks 3D printing potential

Physics-based machine learning unlocks 3D printing potential, thanks to work from Lehigh University's Parisa Khodabakhshi.

MicroCloud Hologram Inc. Releases Hybrid Quantum-Classical Convolutional Neural Network, Achieving New Breakthrough in MNIST Multi-Class Classification

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a Quantum Convolutional Neural Network (QCNN) based on hybrid quantum-classical learning and ...

AI In Manufacturing: Moving Beyond The Hype To Real Business Value

The rise of AI adoption in manufacturing is real, but it's being driven by business outcomes, not technological complexity.
Department of Computer Science - University of Texas at Austin

10 Computer Science Students Selected for New Amazon AI PhD Fellowship

Amazon just announced its new AI PhD Fellowship program, which will provide two years of funding for more than 100 PhD ...
C&EN

Machine Learning-Driven Global Optimization of Single-Atom Catalyst-Mediated Advanced Oxidation Processes

School of Environmental Science and Engineering/Tianjin Research Center for Safe Disposal of Organic Solid Waste and Energy Utilization Engineering, Tianjin University, Tianjin 300072, China ...
IEEE

Learning-Driven Berth Allocation Optimization With Port Authority Behavior

Abstract: This study presents a two-phase framework that integrates machine learning with optimization modeling considering port authority behavior. First, a machine learning model predicts port ...
IEEE

Stochastic Frank-Wolfe Algorithm for Constrained Bilevel Optimization With Improved Per-Iteration Complexity

Abstract: Bilevel optimization, where one optimization problem is inherently nested within another, has gained significant attention due to its extensive applications in machine learning, such as ...
Frontiers

Pipeline monitoring data recovery using novel deep learning models: an engineering case study

Pipeline monitoring frequently encounters missing data, leading to incomplete evaluation and hindering a comprehensive assessment of the pipeline’s structural health. To address this issue, this study ...