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Comparison of echelle spectra to synthetic models has become a computational statistics challenge, with over ten thousand individual spectral lines affecting a typical cool star echelle spectrum. Telluric artifacts, imperfect line lists,…
Metal electrodes are a universal element of all electronic devices. Conducting SrRuO3 (SRO) epitaxial thin films have been extensively used as electrodes in complex-oxide heterostructures due to good lattice mismatches with perovskite…
Using high quality undoped GaAs/AlGaAs heterostructures with optically patterned insulation between two layers of gates, it is possible to investigate very low density mesoscopic regions where the number of impurities is well quantified.…
Interpretability is a pressing issue for machine learning. Common approaches to interpretable machine learning constrain interactions between features of the input, rendering the effects of those features on a model's output comprehensible…
From self-driving vehicles and back-flipping robots to virtual assistants who book our next appointment at the hair salon or at that restaurant for dinner - machine learning systems are becoming increasingly ubiquitous. The main reason for…
We report a method to obtain insights into lower thermal conductivity of \beta-Ga2O3 thin films grown by molecular beam epitaxy (MBE) on c-plane sapphire and 4H-SiC substrates. We compare experimental values against the numerical…
The modelling of interface migration and the associated diffusion mechanisms at the nanoscale level is a challenging issue. For many technological applications ranging from nanoelectronic devices to solar cells, more knowledge of the…
Optimal growth of structures governed by spatially stochastic dynamics arises in many scientific settings, for example in processes such as solution-based crystallization and the formation of microbial biofilms on patterned substrates or…
Learning-based approaches have achieved remarkable performance in the domain of autonomous driving. Leveraging the impressive ability of neural networks and large amounts of human driving data, complex patterns and rules of driving behavior…
Interpretable deep learning is a fundamental building block towards safer AI, especially when the deployment possibilities of deep learning-based computer-aided medical diagnostic systems are so eminent. However, without a computational…
We investigate a stochastic heat engine based on an over-damped particle diffusing on the positive real axis in an externally driven time-periodic log-harmonic potential. The periodic driving is composed of two isothermal and two adiabatic…
Gradient-based approaches in reinforcement learning (RL) have achieved tremendous success in learning policies for autonomous vehicles. While the performance of these approaches warrants real-world adoption, these policies lack…
We have developed an approach to grow high quality ultrathin films of La$_{2-x}$Sr$_x$CuO$_{4}$ with molecular beam epitaxy, by adding a homoepitaxial buffer layer in order to minimize the degradation of the film structure at the interface.…
As an increasingly powerful technique in integrated photonics, inverse design uses optimization algorithms to automatically create compact, high-performance photonic structures, often yielding non-intuitive layouts far more compact than…
We report the growth of epitaxial LaInO3 on DyScO3(110) substrates by adsorption-controlled plasma-assisted molecular beam epitaxy (PA-MBE). The adsorption-controlled growth was monitored using line-of-sight quadrupole mass spectrometry. In…
Many real-world problems are usually computationally costly and the objective functions evolve over time. Data-driven, a.k.a. surrogate-assisted, evolutionary optimization has been recognized as an effective approach for tackling expensive…
Exponential growth in Electronic Healthcare Records (EHR) has resulted in new opportunities and urgent needs for discovery of meaningful data-driven representations and patterns of diseases in Computational Phenotyping research. Deep…
This work introduces a novel interpretable machine learning method called Mixture of Decision Trees (MoDT). It constitutes a special case of the Mixture of Experts ensemble architecture, which utilizes a linear model as gating function and…
Feedback optimization enables autonomous optimality seeking of a dynamical system through its closed-loop interconnection with iterative optimization algorithms. Among various iteration structures, model-based approaches require the…
Superconducting epitaxial FeSe0.5Te0.5 thin films were prepared on SrTiO3 (001) substrates by pulsed laser deposition. The high purity of the phase, the quality of the growth and the epitaxy were studied with different experimental…