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By employing a mixed SnO$_2$+Sn source, we demonstrate suboxide molecular beam epitaxy growth of phase-pure single crystalline metastable SnO(001) thin films at a growth rate of ~1.0nm/min without the need for additional oxygen. These films…

The integration of the Internet of Robotic Things (IoRT) in smart greenhouses has revolutionised precision agriculture by enabling efficient and autonomous environmental control. However, existing time series forecasting models in such…

Machine Learning · Computer Science 2025-12-16 Muhammad Jawad Bashir , Shagufta Henna , Eoghan Furey

We employ an evolutionary optimization framework that perturbs initial states to generate informative and diverse policy demonstrations. A joint surrogate fitness function guides the optimization by combining local diversity, behavioral…

Machine Learning · Computer Science 2025-04-22 Philipp Altmann , Céline Davignon , Maximilian Zorn , Fabian Ritz , Claudia Linnhoff-Popien , Thomas Gabor

Developing tailored semiconductor heterostructures on demand represents a critical capability for addressing the escalating performance demands in electronic and optoelectronic devices. However, traditional fabrication methods remain…

This paper introduces a growth method---suboxide molecular-beam epitaxy (S-MBE)---which enables the growth of Ga2O3 and related materials at growth rates exceeding 1 micrometer per hours with excellent crystallinity in an…

How to interpret a data mining model has received much attention recently, because people may distrust a black-box predictive model if they do not understand how the model works. Hence, it will be trustworthy if a model can provide…

Machine Learning · Computer Science 2025-03-20 Zengyou He , Pengju Li , Yifan Tang , Lianyu Hu , Mudi Jiang , Yan Liu

The dynamic Schr\"odinger bridge problem provides an appealing setting for solving constrained time-series data generation tasks posed as optimal transport problems. It consists of learning non-linear diffusion processes using efficient…

Machine Learning · Computer Science 2023-11-27 Ella Tamir , Martin Trapp , Arno Solin

Given the central role of green e-molecule imports in the European energy transition, many studies optimize import pathways and identify a single cost-optimal solution. However, cost optimality is fragile, as real-world implementation…

Systems and Control · Electrical Eng. & Systems 2025-12-30 Mahdi Kchaou , Francesco Contino , Diederik Coppitters

The development of epitaxy techniques for localized growth of crystalline silicon nanofilms and nanostructures has been crucial to recent advances in electronics and photonics. A precise definition of the crystal growth location, however,…

Materials Science · Physics 2021-09-22 Thomas Reichenbach , Gianpietro Moras , Lars Pastewka , Michael Moseler

An important factor in the practical implementation of optimization models is the acceptance by the intended users. This is influenced among other factors by the interpretability of the solution process. Decision rules that meet this…

Machine Learning · Computer Science 2024-12-03 Marc Goerigk , Michael Hartisch , Sebastian Merten

To make full use of photocathode material and improve its quantum efficiency lifetime, it can be necessary to operate laser away from the cathode center in photoinjectors. In RF guns, the off-axis emitted beam will see a time-dependent RF…

Accelerator Physics · Physics 2016-12-21 Rui-Xuan Huang , Chad Mitchell , Qi-Ka Jia , Christos Papadopoulos , Fernando Sannibale

A crucial problem in achieving innovative high-throughput materials growth with machine learning and automation techniques, such as Bayesian optimization (BO) and robotic experimentation, has been a lack of an appropriate way to handle…

Building generalizable AI models is one of the primary challenges in the healthcare domain. While radiologists rely on generalizable descriptive rules of abnormality, Neural Network (NN) models suffer even with a slight shift in input…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Shantanu Ghosh , Ke Yu , Kayhan Batmanghelich

Mechanistic interpretability has transformed the analysis of transformer circuits by decomposing model behavior into competing algorithms, identifying phase transitions during training, and deriving closed-form predictions for when and why…

Machine Learning · Computer Science 2026-03-19 Alma Lago

Mn-doped GaAs nanowires were grown in the self-catalytic growth mode on oxidized Si(100) surface by molecular beam epitaxy and characterized by scanning and transmission electron microscopy, Raman scattering, photoluminescence,…

Rule-based models, e.g., decision trees, are widely used in scenarios demanding high model interpretability for their transparent inner structures and good model expressivity. However, rule-based models are hard to optimize, especially on…

Machine Learning · Computer Science 2024-01-31 Zhuo Wang , Wei Zhang , Ning Liu , Jianyong Wang

Biofilm growth and transport in confined systems frequently occur in natural and engineered systems. Designing customizable engineered porous materials for controllable biofilm transportation properties could significantly improve the rapid…

Biological Physics · Physics 2023-10-10 Hanfeng Zhai , Jingjie Yeo

It is often the case that the computed optimal solution of an optimization problem cannot be implemented directly, irrespective of data accuracy, due to either (i) technological limitations (such as physical tolerances of machines or…

Optimization and Control · Mathematics 2014-05-21 Han Men , Robert M. Freund , Ngoc C. Nguyen , Joel Saa-Seoane , Jaime Peraire

The epitaxial growth of technically-important $\beta$-Ga$_2$O$_3$ semiconductor thin films have not been realized on flexible substrates due to limitations by the high-temperature crystallization conditions and the lattice-matching…

Personalized treatment decisions have become an integral part of modern medicine. Thereby, the aim is to make treatment decisions based on individual patient characteristics. Numerous methods have been developed for learning such policies…

Machine Learning · Statistics 2023-06-27 Daniel Tschernutter , Tobias Hatt , Stefan Feuerriegel