Millner, Gerfried Mücke, Manfred Romaner, Lorenz Scheiber, Daniel
Published in
Modelling and Simulation in Materials Science and Engineering
In this work we apply data-driven models for predicting tensile strength of steel coils from chemical composition and process parameters. The data originates from steel production and includes a full chemical analysis, as well as many process parameters and the resulting strength properties from tensile tests. We establish a data pre-processing pip...
Frazer, Lance Kote, Vivek Hostetler, Zachary Davis, Matthew Nicolella, Daniel P
Published in
Computer methods in biomechanics and biomedical engineering
Fast-running surrogate computational models (simpler computational models) have been successfully used to replace time-intensive finite element models. However, it is unclear how well they perform in accurately and efficiently replicating complex, full human body finite element models. Here we survey several surrogate modeling techniques and assess...
Coppard, Valerie Szep, Grisha Georgieva, Zoya Howlett, Sarah K. Jarvis, Lorna B. Rainbow, Daniel B. Suchanek, Ondrej Needham, Edward J. Mousa, Hani S. Menon, David K.
...
Published in
Frontiers in Immunology
As the dimensionality, throughput and complexity of cytometry data increases, so does the demand for user-friendly, interactive analysis tools that leverage high-performance machine learning frameworks. Here we introduce FlowAtlas: an interactive web application that enables dimensionality reduction of cytometry data without down-sampling and that ...
Coppard, Valerie Szep, Grisha Georgieva, Zoya Howlett, Sarah K Jarvis, Lorna B Rainbow, Daniel B Suchanek, Ondrej Needham, Edward J Mousa, Hani S Menon, David K
...
As the dimensionality, throughput and complexity of cytometry data increases, so does the demand for user-friendly, interactive analysis tools that leverage high-performance machine learning frameworks. Here we introduce FlowAtlas: an interactive web application that enables dimensionality reduction of cytometry data without down-sampling and that ...
nguyen, dominik
Tato práce zkoumá použití náhodných vnoření v evolučních optimalizačních algoritmech k řešení problémů vysokodimenzionálních optimalizací typu černé skříňky. Za pomocí vnoření vysokodimenzionálních prostorů do prostorů s nižší dimenzí chceme zlepšit výkonnost a efektivitu optimalizačních algoritmů. Naše obsáhlé experimenty demonstrují dosud neprozk...
Cao, Harvey Angelakis, Dimitris G Leykam, Daniel
Published in
Machine Learning: Science and Technology
Quantum many-body scarred systems contain both thermal and non-thermal scar eigenstates in their spectra. When these systems are quenched from special initial states which share high overlap with scar eigenstates, the system undergoes dynamics with atypically slow relaxation and periodic revival. This scarring phenomenon poses a potential avenue fo...
Hernández-León, Patricia Caro, Miguel A
Published in
Physica Scripta
We present a new technique for visualizing high-dimensional data called cluster MDS (cl-MDS), which addresses a common difficulty of dimensionality reduction methods: preserving both local and global structures of the original sample in a single 2-dimensional visualization. Its algorithm combines the well-known multidimensional scaling (MDS) tool w...
Floris, Mihnea (author)
This research contributes to addressing climate change challenges through the examination of hydrogen combustion. It investigates the flow dynamics within a simplified model of Ansaldo Energia's GT36 reheat combustor using Large Eddy Simulation (LES) at a high pressure of 20 bar, focusing on the autoignition flashback phenomena observed. More speci...
Bauman, Nicholas P
Published in
Electronic Structure
Downfolding coupled cluster (CC) techniques are powerful tools for reducing the dimensionality of many-body quantum problems. This work investigates how ground-state downfolding formalisms can target excited states using non-Aufbau reference determinants, paving the way for applications of quantum computing in excited-state chemistry. This study fo...
Coppard, Valerie Szep, Grisha Georgieva, Zoya Howlett, Sarah K Jarvis, Lorna B Rainbow, Daniel B Suchanek, Ondrej Needham, Edward J Mousa, Hani S Menon, David K
...
Peer reviewed: True / Acknowledgements: We thank the deceased organ donors, donor families, the extended Cambridge Biorepository for Translational Medicine team, and the transplant coordinators for access to the tissue samples. We thank Aaditya Prabhu, who generated the large dataset we used for FlowAtlas stress testing. We specially thank Professo...
