Zobrazeno 1 - 10
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pro vyhledávání: '"von Brecht, James H."'
We study a class of minimal geometric partial differential equations that serves as a framework to understand the evolution of boundaries between states in different pattern forming systems. The framework combines normal growth, curvature flow and no
Externí odkaz:
http://arxiv.org/abs/2311.01633
We formalize and study a phenomenon called feature collapse that makes precise the intuitive idea that entities playing a similar role in a learning task receive similar representations. As feature collapse requires a notion of task, we leverage a si
Externí odkaz:
http://arxiv.org/abs/2305.16162
We propose a simple data model inspired from natural data such as text or images, and use it to study the importance of learning features in order to achieve good generalization. Our data model follows a long-tailed distribution in the sense that som
Externí odkaz:
http://arxiv.org/abs/2205.14553
Autor:
von Brecht, James H., Blair, Ryan
We study a class of nonlocal, energy-driven dynamical models that govern the motion of closed, embedded curves from both an energetic and dynamical perspective. Our energetic results provide a variety of ways to understand physically motivated energe
Externí odkaz:
http://arxiv.org/abs/1711.08104
Ideas from the image processing literature have recently motivated a new set of clustering algorithms that rely on the concept of total variation. While these algorithms perform well for bi-partitioning tasks, their recursive extensions yield unimpre
Externí odkaz:
http://arxiv.org/abs/1306.1185
We propose an adaptive version of the total variation algorithm proposed in [3] for computing the balanced cut of a graph. The algorithm from [3] used a sequence of inner total variation minimizations to guarantee descent of the balanced cut energy a
Externí odkaz:
http://arxiv.org/abs/1302.2717
Unsupervised clustering of scattered, noisy and high-dimensional data points is an important and difficult problem. Tight continuous relaxations of balanced cut problems have recently been shown to provide excellent clustering results. In this paper,
Externí odkaz:
http://arxiv.org/abs/1204.6545
Autor:
von Brecht, James H.
Publikováno v:
In Journal of Differential Equations 15 January 2016 260(2):1622-1655
Publikováno v:
In Journal of Computational Physics 2010 229(18):6405-6426
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