Zobrazeno 1 - 10
of 197
pro vyhledávání: '"Murray, Ryan P."'
Autor:
Murray, Ryan, Pickarski, Adam
This work considers large-data asymptotics for t-distributed stochastic neighbor embedding (tSNE), a widely-used non-linear dimension reduction algorithm. We identify an appropriate continuum limit of the tSNE objective function, which can be viewed
Externí odkaz:
http://arxiv.org/abs/2410.13063
Autor:
Wilcox, Galen, Murray, Ryan
We represent the outermost shear interface of an eddy by a circular vortex sheet in two dimensions, and provide a new proof of linear instability via the Birkhoff-Rott equation. Like planar vortex sheets, circular sheets are found to be susceptible t
Externí odkaz:
http://arxiv.org/abs/2408.08220
Autor:
Murray, Ryan, Pickarski, Adam
Dimension reduction algorithms are a crucial part of many data science pipelines, including data exploration, feature creation and selection, and denoising. Despite their wide utilization, many non-linear dimension reduction algorithms are poorly und
Externí odkaz:
http://arxiv.org/abs/2408.02433
Autor:
Morris, Rachel, Murray, Ryan
In recent years there has been significant interest in the effect of different types of adversarial perturbations in data classification problems. Many of these models incorporate the adversarial power, which is an important parameter with an associa
Externí odkaz:
http://arxiv.org/abs/2406.14682
We introduce a local-in-time existence and uniqueness class for solutions to the 2d Euler equation with unbounded vorticity. Furthermore, we show that solutions belonging to this class can develop stronger singularities in finite time, meaning that t
Externí odkaz:
http://arxiv.org/abs/2312.17610
Autor:
Miller, Kevin, Murray, Ryan
This work introduces Dirichlet Active Learning (DiAL), a Bayesian-inspired approach to the design of active learning algorithms. Our framework models feature-conditional class probabilities as a Dirichlet random field and lends observational strength
Externí odkaz:
http://arxiv.org/abs/2311.05501
The rapid advancement of Generative Adversarial Networks (GANs) necessitates the need to robustly evaluate these models. Among the established evaluation criteria, the Fr\'{e}chetInception Distance (FID) has been widely adopted due to its conceptual
Externí odkaz:
http://arxiv.org/abs/2310.20636
Autor:
Murray, Ryan, Wilcox, Galen
We study the evolution of vortex sheets according to the Birkhoff-Rott equation, which describe the motion of sharp shear interfaces governed by the incompressible Euler equation in two dimensions. In a recent work, the authors demonstrated within th
Externí odkaz:
http://arxiv.org/abs/2301.01659
We study the long-time behavior of scale-invariant solutions of the 2d Euler equation satisfying a discrete symmetry. We show that all scale-invariant solutions with bounded variation on $\mathbb{S}^1$ relax to states that are piece-wise constant wit
Externí odkaz:
http://arxiv.org/abs/2211.08418
Autor:
Murray, Ryan, Wilcox, Galen
This article revisits the instability of sharp shear interfaces, also called vortex sheets, in incompressible fluid flows. We study the Birkhoff-Rott equation, which describes the motion of vortex sheets according to the incompressible Euler equation
Externí odkaz:
http://arxiv.org/abs/2211.03585