Zobrazeno 1 - 10
of 1 232
pro vyhledávání: '"Kim Dohyun"'
Autor:
Kim, Dohyun, Shim, Woojoo
The aim of this article is to investigate the convergence properties of a heterogeneous consensus model on Stiefel manifolds. We consider each agent, without interaction, moving according to the flow determined by the fundamental vector field of the
Externí odkaz:
http://arxiv.org/abs/2412.18923
We introduce a novel method for solving density-based topology optimization problems: Sigmoidal Mirror descent with a Projected Latent variable (SiMPL). The SiMPL method (pronounced as "the simple method") optimizes a design using only first-order de
Externí odkaz:
http://arxiv.org/abs/2411.19421
In this paper, C1-conforming element methods are analyzed for the stream function formulation of a single layer non-stationary quasi-geostrophic equation in the ocean circulation model. In its first part, some new regularity results are derived, whic
Externí odkaz:
http://arxiv.org/abs/2411.10732
Autor:
Kim, Dohyun, Sandoval-Segura, Pedro
The construction of large datasets for deep learning has raised concerns regarding unauthorized use of online data, leading to increased interest in protecting data from third-parties who want to use it for training. The Convolution-based Unlearnable
Externí odkaz:
http://arxiv.org/abs/2411.01742
We present a rigorous convergence analysis of a new method for density-based topology optimization: Sigmoidal Mirror descent with a Projected Latent variable. SiMPL, pronounced like "simple," provides point-wise bound preserving design updates and fa
Externí odkaz:
http://arxiv.org/abs/2409.19341
Autor:
Kim, Dohyun
Geometrical interpretation on U(1) gage theory of Dirac monopole, introduced here from the line integral\cite{Brandt} form of vector potentials, shows the gauge representation be multi-valued. In this paper, we construct Euclidean form of U(1) gauge
Externí odkaz:
http://arxiv.org/abs/2404.17786
In recent years, the integration of large language models (LLMs) has revolutionized the field of robotics, enabling robots to communicate, understand, and reason with human-like proficiency. This paper explores the multifaceted impact of LLMs on robo
Externí odkaz:
http://arxiv.org/abs/2404.09228
Autor:
Andrej, Julian, Atallah, Nabil, Bäcker, Jan-Phillip, Camier, John, Copeland, Dylan, Dobrev, Veselin, Dudouit, Yohann, Duswald, Tobias, Keith, Brendan, Kim, Dohyun, Kolev, Tzanio, Lazarov, Boyan, Mittal, Ketan, Pazner, Will, Petrides, Socratis, Shiraiwa, Syun'ichi, Stowell, Mark, Tomov, Vladimir
The MFEM (Modular Finite Element Methods) library is a high-performance C++ library for finite element discretizations. MFEM supports numerous types of finite element methods and is the discretization engine powering many computational physics and en
Externí odkaz:
http://arxiv.org/abs/2402.15940
We aim to solve the problem of spatially localizing composite instructions referring to space: space grounding. Compared to current instance grounding, space grounding is challenging due to the ill-posedness of identifying locations referred to by di
Externí odkaz:
http://arxiv.org/abs/2402.01183
Autor:
Dzanic, Tarik, Mittal, Ketan, Kim, Dohyun, Yang, Jiachen, Petrides, Socratis, Keith, Brendan, Anderson, Robert
We introduce DynAMO, a reinforcement learning paradigm for Dynamic Anticipatory Mesh Optimization. Adaptive mesh refinement is an effective tool for optimizing computational cost and solution accuracy in numerical methods for partial differential equ
Externí odkaz:
http://arxiv.org/abs/2310.01695