Results 281 to 290 of about 820,067 (303)
Some of the next articles are maybe not open access.
Science, 2022
Seismic waves from earthquakes and other sources are used to infer the structure and properties of Earth’s interior. The availability of large-scale seismic datasets and the suitability of deep-learning techniques for seismic data processing have pushed deep learning to the forefront of fundamental, long-standing research investigations in seismology ...
S. Mostafa Mousavi, Gregory C. Beroza
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Seismic waves from earthquakes and other sources are used to infer the structure and properties of Earth’s interior. The availability of large-scale seismic datasets and the suitability of deep-learning techniques for seismic data processing have pushed deep learning to the forefront of fundamental, long-standing research investigations in seismology ...
S. Mostafa Mousavi, Gregory C. Beroza
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2019
The chapter is devoted at illustrating the basic principles and the current results which characterize the research on Deep Learning. The term refers to the theory and practice of devising and training complex neural networks for supervised and unsupervised tasks.
Massimo Guarascio +2 more
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The chapter is devoted at illustrating the basic principles and the current results which characterize the research on Deep Learning. The term refers to the theory and practice of devising and training complex neural networks for supervised and unsupervised tasks.
Massimo Guarascio +2 more
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2023
Offering a variety of connectionist models that are representative of the state-of-the-art, this textbook provides a succinct, accessible, and interesting first introduction to deep learning. The work takes a user-friendly approach to examining today's top algorithms and architectures, walking readers through the arithmetic behind each concept as it is
Niranchana Shri Viswanathan +3 more
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Offering a variety of connectionist models that are representative of the state-of-the-art, this textbook provides a succinct, accessible, and interesting first introduction to deep learning. The work takes a user-friendly approach to examining today's top algorithms and architectures, walking readers through the arithmetic behind each concept as it is
Niranchana Shri Viswanathan +3 more
+4 more sources
Nature Computational Science, 2021
The computational complexity of deep neural networks is a major obstacle of many application scenarios driven by low-power devices, including federated learning. A recent finding shows that random sketches can substantially reduce the model complexity without affecting prediction accuracy.
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The computational complexity of deep neural networks is a major obstacle of many application scenarios driven by low-power devices, including federated learning. A recent finding shows that random sketches can substantially reduce the model complexity without affecting prediction accuracy.
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Deep Questioning and Deep Learning
Academic Radiology, 2012T here is relatively strong empirical evidence that an effective means of enhancing learner performance is to pose ‘‘deep questions’’ (1). Examples of deep questioning include asking learners to explore the causes of a sequence of events, the motivations of the people involved, or the quality of the evidence behind a particular practice or theory.
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2023
We have developed this volume, Deep Reading, Deep Learning, as a companion to our 2017 NCTE book, Deep Reading: Teaching Reading in the Writing Classroom, which received the CCCC Outstanding Book Award in 2019 for Best Edited Collection. In this volume we address a range of social, ethical, and pedagogical issues that have emerged as essential concerns
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We have developed this volume, Deep Reading, Deep Learning, as a companion to our 2017 NCTE book, Deep Reading: Teaching Reading in the Writing Classroom, which received the CCCC Outstanding Book Award in 2019 for Best Edited Collection. In this volume we address a range of social, ethical, and pedagogical issues that have emerged as essential concerns
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SIGGRAPH Asia 2019 Courses, 2018
Concepts, terminology, structures, no math, no code. Free open-source libraries do the hard work. My background: consultant, writer, director, etc.
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Concepts, terminology, structures, no math, no code. Free open-source libraries do the hard work. My background: consultant, writer, director, etc.
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Deep Eutectic Solvents: A Review of Fundamentals and Applications
Chemical Reviews, 2021Brian Chen, Yong Zhang, Jeffrey M Klein
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