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Numerical behavior of NVIDIA tensor cores [PDF]
PeerJ Computer Science, 2021 We explore the floating-point arithmetic implemented in the NVIDIA tensor cores, which are hardware accelerators for mixed-precision matrix multiplication available on the Volta, Turing, and Ampere microarchitectures.
Massimiliano Fasi +3 more
doaj +6 more sources
An AI-based mental health guardrail and dataset for identifying psychiatric crises in text-based conversations [PDF]
npj Digital MedicineLarge language models often mishandle psychiatric emergencies, offering harmful or inappropriate advice. This study evaluated the Verily Mental Health Guardrail (VMHG) on two clinician-labeled datasets: the Verily Mental Health Crisis Dataset v1.0 ...
Benjamin W. Nelson +8 more
doaj +2 more sources
Going to Extremes: Weakly Supervised Medical Image Segmentation
Machine Learning and Knowledge Extraction, 2021 Medical image annotation is a major hurdle for developing precise and robust machine-learning models. Annotation is expensive, time-consuming, and often requires expert knowledge, particularly in the medical field.
Holger R. Roth +4 more
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The NVIDIA PilotNet Experiments
CoRR, 2020 Four years ago, an experimental system known as PilotNet became the first NVIDIA system to steer an autonomous car along a roadway. This system represents a departure from the classical approach for self-driving in which the process is manually decomposed into a series of modules, each performing a different task.
Mariusz Bojarski +24 more
openaire +2 more sources
, 2023 Despite their resource- and power-constrained nature, edge devices also exhibit an increase in the available compute and memory resources and heterogeneity, similar to the evolution of server hardware in the past decade. For example, NVIDIA Jetson devices have a system-on-chip (SoC) composed of an ARM CPU and an NVIDIA GPU sharing RAM that could be up ...
Robert Bayer +2 more
openaire +3 more sources
The future of digital health with federated learning
npj Digital Medicine, 2020 Data-driven machine learning (ML) has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes by modern healthcare systems.
Nicola Rieke +16 more
doaj +1 more source
Improving Individual Brain Age Prediction Using an Ensemble Deep Learning Framework
Frontiers in Psychiatry, 2021 Brain age is an imaging-based biomarker with excellent feasibility for characterizing individual brain health and may serve as a single quantitative index for clinical and domain-specific usage.
Chen-Yuan Kuo +13 more
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Deep learning-based enhancement of epigenomics data with AtacWorks
Nature Communications, 2021 ATAC-seq measures chromatin accessibility as a proxy for the activity of DNA regulatory regions across the genome. Here the authors present AtacWorks, a deep learning tool to denoise and identify accessible chromatin regions from low cell count, low ...
Avantika Lal +5 more
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A large language model for electronic health records
npj Digital Medicine, 2022 There is an increasing interest in developing artificial intelligence (AI) systems to process and interpret electronic health records (EHRs). Natural language processing (NLP) powered by pretrained language models is the key technology for medical AI ...
Xi Yang +18 more
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The Effect of Earnings Announcement on the Market Value of Corporate Stock [PDF]
Облік і фінансиOn June 18, 2024, Nvidia's stock was momentarily crowned as the world's most valuable stock – surpassing other technology companies. Accordingly, this paper aims to analyze the differential effect of Nvidia's earnings announcement on the company's stock ...
Collins C Ngwakwe
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