Results 11 to 20 of about 1,248,762 (236)
Applying a random projection algorithm to optimize machine learning model for predicting peritoneal metastasis in gastric cancer patients using CT images [PDF]
Comput. Methods Programs Biomed., 2020 BACKGROUND AND OBJECTIVE Non-invasively predicting the risk of cancer metastasis before surgery can play an essential role in determining which patients can benefit from neoadjuvant chemotherapy.
Seyedehnafiseh Mirniaharikandehei +10 more
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Philosophy of science at sea: Clarifying the interpretability of machine learning
Philosophy Compass, 2022 In computer science, there are efforts to make machine learning more interpretable or explainable, and thus to better understand the underlying models ...
C. Beisbart, Tim Räz
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A general guide to applying machine learning to computer architecture [PDF]
, 2018 The resurgence of machine learning since the late 1990s has been enabled by significant advances in computing performance and the growth of big data.
Arkose, Tugberk +6 more
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Discriminative Cooperative Networks for Detecting Phase Transitions [PDF]
, 2018 The classification of states of matter and their corresponding phase transitions is a special kind of machine-learning task, where physical data allow for the analysis of new algorithms, which have not been considered in the general computer-science ...
Liu, Ye-Hua +1 more
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Big data and machine learning for materials science
Discover Materials, 2021 Herein, we review aspects of leading-edge research and innovation in materials science that exploit big data and machine learning (ML), two computer science concepts that combine to yield computational intelligence.
J. F. Rodrigues +4 more
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A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems [PDF]
, 2019 We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation.
Teije, Annette ten, van Harmelen, Frank
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Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy [PDF]
, 2017 Astrophysics and cosmology are rich with data. The advent of wide-area digital cameras on large aperture telescopes has led to ever more ambitious surveys of the sky.
Gieseke, Fabian +4 more
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DScribe: Library of Descriptors for Machine Learning in Materials Science [PDF]
Computer Physics Communications, 2019 DScribe is a software package for machine learning that provides popular feature transformations ("descriptors") for atomistic materials simulations. DScribe accelerates the application of machine learning for atomistic property prediction by providing ...
Lauri Himanen +7 more
semanticscholar +1 more source
Iraqi Journal for Computer Science and Mathematics, 2023 People in the modern era spend most of their lives in virtual environments that offer a range of public and private services and social platforms. Therefore, these environments need to be protected from cyber attackers that can steal data or disrupt ...
Maad M. Mijwil
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Machine Learning Bell Nonlocality in Quantum Many-body Systems
, 2017 Machine learning, the core of artificial intelligence and big data science, is one of today's most rapidly growing interdisciplinary fields. Recently, its tools and techniques have been adopted to tackle intricate quantum many-body problems. In this work,
Deng, Dong-Ling
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