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检索条件"机构=Division of Computing and Data Science"
405 条 记 录,以下是91-100 订阅
排序:
Label-independent hyperparameter-free self-supervised single-view deep subspace clustering
arXiv
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arXiv 2025年
作者: Sindičić, Lovro Kopriva, Ivica Division of Computing and Data Science Ruđer Bošković Institute Bijenička cesta 54 Zagreb10000 Croatia
Deep subspace clustering (DSC) algorithms face several challenges that hinder their widespread adoption across various application domains. First, clustering quality is typically assessed using only the encoder’s out... 详细信息
来源: 评论
CaloScore v2: Single-shot Calorimeter Shower Simulation with Diffusion Models
arXiv
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arXiv 2023年
作者: Mikuni, Vinicius Nachman, Benjamin National Energy Research Scientific Computing Center Berkeley Lab BerkeleyCA94720 United States Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States
Diffusion generative models are promising alternatives for fast surrogate models, producing high-fidelity physics simulations. However, the generation time often requires an expensive denoising process with hundreds o... 详细信息
来源: 评论
High-dimensional and Permutation Invariant Anomaly Detection
arXiv
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arXiv 2023年
作者: Mikuni, Vinicius Nachman, Benjamin National Energy Research Scientific Computing Center Berkeley Lab BerkeleyCA94720 United States Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States
Methods for anomaly detection of new physics processes are often limited to low-dimensional spaces due to the difficulty of learning high-dimensional probability densities. Particularly at the constituent level, incor... 详细信息
来源: 评论
Machine Learned Potential for High-Throughput Phonon Calculations of Metal–Organic Frameworks
arXiv
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arXiv 2024年
作者: Elena, Alin Marin Kamath, Prathami Divakar Inizan, Théo Jaffrelot Rosen, Andrew S. Zanca, Federica Persson, Kristin A. Scientific Computing Department Science and Technology Facilities Council Keckwick Lane Daresbury Cheshire WA4 1PT United Kingdom Department of Materials Science and Engineering University of California BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Bakar Institute of Digital Materials for the Planet College of Computing Data Science and Society University of California BerkeleyCA94720 United States Department of Chemical and Biological Engineering Princeton University PrincetonNJ08544 United States
Metal–organic frameworks (MOFs) are highly porous and versatile materials studied extensively for applications such as carbon capture and water harvesting. However, computing phonon-mediated properties in MOFs, like ... 详细信息
来源: 评论
Refining Fast Calorimeter Simulations with a Schrödinger Bridge
arXiv
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arXiv 2023年
作者: Diefenbacher, Sascha Mikuni, Vinicius Nachman, Benjamin Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States National Energy Research Scientific Computing Center Berkeley Lab BerkeleyCA94720 United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States
Machine learning-based simulations, especially calorimeter simulations, are promising tools for approximating the precision of classical high energy physics simulations with a fraction of the generation time. Nearly a... 详细信息
来源: 评论
Discriminative versus Generative Approaches to Simulation-based Inference
arXiv
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arXiv 2025年
作者: Sluijter, Benjamin Diefenbacher, Sascha Bhimji, Wahid Nachman, Benjamin Leiden Institute of Physics Universiteit Leiden Leiden2300 RA Netherlands Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States National Energy Research Scientific Computing Center Berkeley Lab BerkeleyCA94720 United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States
Most of the fundamental, emergent, and phenomenological parameters of particle and nuclear physics are determined through parametric template fits. Simulations are used to populate histograms which are then matched to... 详细信息
来源: 评论
Shape-guided Conditional Latent Diffusion Models for Synthesising Brain Vasculature
arXiv
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arXiv 2023年
作者: Deo, Yash Dou, Haoran Ravikumar, Nishant Frangi, Alejandro F. Lassila, Toni School of Computing and School of Medicine University of Leeds Leeds United Kingdom Leeds United Kingdom Alan Turing Institute London United Kingdom Electrical Engineering and Cardiovascular Sciences Departments Ku Leuven Leuven Belgium Division of Informatics Imaging and Data Science Schools of Computer Science and Health Sciences University of Manchester Manchester United Kingdom
The Circle of Willis (CoW) is the part of cerebral vasculature responsible for delivering blood to the brain. Understanding the diverse anatomical variations and configurations of the CoW is paramount to advance resea... 详细信息
来源: 评论
Predicting Risk of Dementia with Survival Machine Learning and Statistical Methods: Results on the English Longitudinal Study of Ageing Cohort
arXiv
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arXiv 2023年
作者: Stamate, Daniel Musto, Henry Ajnakina, Olesya Stahl, Daniel Data Science & Soft Computing Lab Computing Department Goldsmiths College University of London United Kingdom Division of Population Health Health Services Research & Primary Care School of Health Sciences University of Manchester United Kingdom Institute of Psychiatry Psychology and Neuroscience Biostatistics and Health Informatics Department King’s College London United Kingdom Department of Behavioural Science and Health Institute of Epidemiology and Health Care University College London United Kingdom
Machine learning models that aim to predict dementia onset usually follow the classification methodology ignoring the time until an event happens. This study presents an alternative, using survival analysis within the... 详细信息
来源: 评论
Learned Local Attention Maps for Synthesising Vessel Segmentations from T2 MRI
arXiv
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arXiv 2023年
作者: Deo, Yash Bonazzola, Rodrigo Dou, Haoran Xia, Yan Wei, Tianyou Ravikumar, Nishant Frangi, Alejandro F. Lassila, Toni School of Computing and School of Medicine University of Leeds Leeds United Kingdom Leeds United Kingdom Alan Turing Institute London United Kingdom Electrical Engineering and Cardiovascular Sciences Department KU Leuven Leuven Belgium Division of Informatics Imaging and Data Science Schools of Computer Science and Health Sciences University of Manchester Manchester United Kingdom
Magnetic resonance angiography (MRA) is an imaging modality for visualising blood vessels. It is useful for several diagnostic applications and for assessing the risk of adverse events such as haemorrhagic stroke (res... 详细信息
来源: 评论
Score-based generative models for calorimeter shower simulation
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Physical Review D 2022年 第9期106卷 092009-092009页
作者: Vinicius Mikuni Benjamin Nachman National Energy Research Scientific Computing Center Berkeley Lab Berkeley California 94720 USA Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Berkeley Institute for Data Science University of California Berkeley California 94720 USA
Score-based generative models are a new class of generative algorithms that have been shown to produce realistic images even in high dimensional spaces, currently surpassing other state-of-the-art models for different... 详细信息
来源: 评论