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1.
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Genome-wide association studies (GWASs) have been widely applied in the neuroimaging field to discover genetic variants associated with brain-related traits. So far, almo [...]
15 October 2024 |
Article |
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2.
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We consider the analysis of singular waveguides separating insulating phases in two-space dimensions. The insulating domains are modeled by a massive Schrödinger equatio [...]
06 October 2024 |
Computational and Applied Mathematics; Mathematics; Statistics |
Article |
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3.
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Mathematics, as Eugene Wigner once noted, has no inherent reason to be as effective in the natural sciences as it is. Yet, those who seek to model the world have long use [...]
2024-12 |
Computational and Applied Mathematics |
Dissertation |
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4.
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This dissertation delves into statistical inverse problems with a focus on Bayesian approaches for parameter estimation and uncertainty quantification under sparsity, non [...]
2024-06 |
Computational and Applied Mathematics |
Dissertation |
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5.
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This thesis concerns continuous models for 2-dimensional topological insulators. Such systems are characterized by asymmetric transport along a 1-dimensional curve repres [...]
2023-08 |
Computational and Applied Mathematics |
Dissertation |
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6.
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The Ward Hunt and Milne ice shelves are the present-day remnants of a much larger ice shelf that once fringed the coast of Ellesmere Island, Canada. These ice shelves pos [...]
14 August 2023 |
Computational and Applied Mathematics; Geophysical Sciences |
Article |
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7.
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Matrix and tensor operations play a vital role in diverse fields such as machine learning, numerical analysis, computational physics and optimization. As data sizes conti [...]
2023-06 |
Computational and Applied Mathematics |
Dissertation |
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8.
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Inverse problems (IPs) deal with the task of reconstructing input variables from noisy observations, defined through a forward model. When the forward map is known, the r [...]
2023-06 |
Computational and Applied Mathematics |
Dissertation |
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9.
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In this dissertation, we study three problems in nonconvex optimization and matrix computation: rank-constrained hyperbolic programming, real and complex matrix multiplic [...]
2023-06 |
Computational and Applied Mathematics |
Dissertation |
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10.
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Stochastic optimization algorithms have become indispensable in modern machine learning. The developments of theories and algorithms of modern optimization also requires [...]
2023-06 |
Computational and Applied Mathematics |
Dissertation |
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11.
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A causal vector autoregressive (CVAR) model is introduced for weakly stationary multivariate processes, combining a recursive directed graphical model for the contemporan [...]
24 February 2023 |
Computational and Applied Mathematics |
Article |
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12.
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Mass spectrometry is a vital tool in the analytical chemist’s toolkit, commonly used to identify the presence of known compounds and elucidate unknown chemical structur [...]
25 January 2023 |
Computational and Applied Mathematics; Computer Science; Statistics |
Article |
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13.
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Extreme weather events have large consequences, dominating the impact of climate on society, but are very difficult to characterize and predict, being exceptionally rare [...]
2022-08 |
Computational and Applied Mathematics |
Dissertation |
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14.
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Generative models, especially ones that are parametrized by deep neural networks, are powerful unsupervised learning tools towards understanding complex data without labe [...]
2022-06 |
Computational and Applied Mathematics |
Dissertation |
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15.
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Matérn Gaussian fields are popular modeling choices in many aspects of Bayesian inverse problems, spatial statistics, machine learning, and numerous other scientific app [...]
2022-06 |
Computational and Applied Mathematics |
Dissertation |
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16.
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Previously, McPeek and Thornton (2007) developed the MQLS test used to perform a case-control test of association between an autosomal marker and a binary trait in a samp [...]
2009-04 |
Computational and Applied Mathematics; Physical Sciences |
Thesis |
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