Zobrazeno 1 - 10
of 2 969
pro vyhledávání: '"Cloninger, A."'
Autor:
Karris, Nicholas, Nikitopoulos, Evangelos A., Kevrekidis, Ioannis, Lee, Seungjoon, Cloninger, Alexander
We develop an algorithm to approximate the time evolution of a probability measure without explicitly learning an operator that governs the evolution. A particular application of interest is discrete measures $\mu_t^N$ that arise from particle system
Externí odkaz:
http://arxiv.org/abs/2408.01857
We construct and analyze a neural network two-sample test to determine whether two datasets came from the same distribution (null hypothesis) or not (alternative hypothesis). We perform time-analysis on a neural tangent kernel (NTK) two-sample test.
Externí odkaz:
http://arxiv.org/abs/2407.04806
DBSCAN and OPTICS are powerful algorithms for identifying clusters of points in domains where few assumptions can be made about the structure of the data. In this paper, we leverage these strengths and introduce a new algorithm, LINSCAN, designed to
Externí odkaz:
http://arxiv.org/abs/2406.17952
The fields of effective resistance and optimal transport on graphs are filled with rich connections to combinatorics, geometry, machine learning, and beyond. In this article we put forth a bold claim: that the two fields should be understood as one a
Externí odkaz:
http://arxiv.org/abs/2404.15261
Autor:
Pirhadi, Alireza, Moslemi, Mohammad Hossein, Cloninger, Alexander, Milani, Mostafa, Salimi, Babak
Ensuring Conditional Independence (CI) constraints is pivotal for the development of fair and trustworthy machine learning models. In this paper, we introduce \sys, a framework that harnesses optimal transport theory for data repair under CI constrai
Externí odkaz:
http://arxiv.org/abs/2403.02372
Autor:
Cloninger, Jeffrey A., Harris, Raine, Haley, Kristine L., Sterbentz, Randy M., Taniguchi, Takashi, Watanabe, Kenji, Island, Joshua O.
Publikováno v:
2024 J. Phys.: Condens. Matter 36 455301
The use of metal van der Waals contacts and the implicit reduction in Fermi-level pinning in contacted semiconductors has led to remarkable device optimizations. For example, using graphene as an electrical contact allows for tunable Schottky barrier
Externí odkaz:
http://arxiv.org/abs/2402.03611
We introduce Deep Set Linearized Optimal Transport, an algorithm designed for the efficient simultaneous embedding of point clouds into an $L^2-$space. This embedding preserves specific low-dimensional structures within the Wasserstein space while co
Externí odkaz:
http://arxiv.org/abs/2401.01460
We develop a machine learning approach to identifying parameters with steady-state solutions, locating such solutions, and determining their linear stability for systems of ordinary differential equations and dynamical systems with parameters. Our ap
Externí odkaz:
http://arxiv.org/abs/2312.10315
In this paper, we explore the untapped intersection of the graph connection Laplacian and discrete optimal transport to propose a novel framework for studying optimal parallel transport between vector fields on graphs. Our study establishes feasibili
Externí odkaz:
http://arxiv.org/abs/2312.10295
Autor:
Cloninger, Alexander, Mishne, Gal, Oslandsbotn, Andreas, Robertson, Sawyer Jack, Wan, Zhengchao, Wang, Yusu
We investigate the concept of effective resistance in connection graphs, expanding its traditional application from undirected graphs. We propose a robust definition of effective resistance in connection graphs by focusing on the duality of Dirichlet
Externí odkaz:
http://arxiv.org/abs/2308.09690