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by
Balasalle, James, author.
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We show that the parallel derivative methods achieve a high level of parallel efficiency and work
by
Wen, Haiguang, author.
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The overarching objective of this work is to bridge neuroscience and artificial intelligence to
by
Tan, Xi, author.
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characteristics have been largely ignored in previous work. In this dissertation, we address these limitations via
by
Jaegle, Andrew, author.
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, nonrigid world. This work is organized around a view of motion as a global phenomenon that is not
by
Zhang, Jiawei, author.
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not support identifying spatial patterns at varying scales. In this work, we present a context
by
Liu, Tiantian, author.
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relies on Newton's method, which is slow, even with only one iteration per timestep. In this work, we
by
McGinty, Hande Küçük, author.
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they work together in complex queries.
by
Bittner, Rachel, author.
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, there has been relatively little work on data-driven f0 estimation, primarily due to the lack of
by
Oluwatimi, Oyindamola D., author.
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policies that the context-aware systems are able to support and enforce. Specifically, the work proposes
by
Vaiana, Michael, author. (orcid)0000-0002-4955-4114
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scales. In this dissertation, I present work integrating multilayer networks and computational topology
by
Khurana, Dakshita, author.
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rewinding technique is synonymous with protocol security and polynomial simulation. Prior to this work, all
by
Church, Benjamin David, author.
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published work, and modular and incremental developments may improve segmentation generation and

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