Zobrazeno 1 - 10
of 325 525
pro vyhledávání: '"Seong An"'
Autor:
Andrews, Moira, Artale, M. Celeste, Kumar, Ankit, Lee, Kyoung-Soo, Florek, Tess, Anand, Kaustub, Cerdosino, Candela, Ciardullo, Robin, Firestone, Nicole, Gawiser, Eric, Gronwall, Caryl, Guaita, Lucia, Hong, Sungryong, Hwang, Ho Seong, Lee, Jaehyun, Lee, Seong-Kook, Padilla, Nelson, Park, Jaehong, Popescu, Roxana, Ramakrishnan, Vandana, Song, Hyunmi, Cádiz, F. Vivanco, Vogelsberger, Mark
We investigate the physical properties and redshift evolution of simulated galaxies residing in protoclusters at cosmic noon, to understand the influence of the environment on galaxy formation. This work is to build clear expectations for the ongoing
Externí odkaz:
http://arxiv.org/abs/2410.08412
3D point clouds are increasingly vital for applications like autonomous driving and robotics, yet the raw data captured by sensors often suffer from noise and sparsity, creating challenges for downstream tasks. Consequently, point cloud upsampling be
Externí odkaz:
http://arxiv.org/abs/2411.00432
Membership inference attacks (MIA) attempt to verify the membership of a given data sample in the training set for a model. MIA has become relevant in recent years, following the rapid development of large language models (LLM). Many are concerned ab
Externí odkaz:
http://arxiv.org/abs/2411.00154
Autor:
Park, Seong Hyeon, Choi, Gahyun, Kim, Eunjong, Park, Gwanyeol, Choi, Jisoo, Choi, Jiman, Chong, Yonuk, Lee, Yong-Ho, Hahn, Seungyong
Recent advances in quantum information processing with superconducting qubits have fueled a growing demand for scaling and miniaturizing circuit layouts. Despite significant progress, accurately predicting the Hamiltonian of complex circuits remains
Externí odkaz:
http://arxiv.org/abs/2410.24004
Disentangled representation learning (DRL) aims to break down observed data into core intrinsic factors for a profound understanding of the data. In real-world scenarios, manually defining and labeling these factors are non-trivial, making unsupervis
Externí odkaz:
http://arxiv.org/abs/2410.23820
Autor:
Kim, Tae-Geun, Park, Seong Chan
We propose a novel framework based on neural network that reformulates classical mechanics as an operator learning problem. A machine directly maps a potential function to its corresponding trajectory in phase space without solving the Hamilton equat
Externí odkaz:
http://arxiv.org/abs/2410.20951
Autor:
Woo, Soojin, Kim, Seong-Woo
In vision-based robot localization and SLAM, Visual Place Recognition (VPR) is essential. This paper addresses the problem of VPR, which involves accurately recognizing the location corresponding to a given query image. A popular approach to vision-b
Externí odkaz:
http://arxiv.org/abs/2410.19341
We investigate hysteresis in a generalized Kuramoto model with identical oscillators, focusing on coupling strength inhomogeneity, which results in oscillators being coupled to others with varying strength, and a simplified, more realistic coupling f
Externí odkaz:
http://arxiv.org/abs/2410.18515
Futaki invariants of the classical moduli space of 4d N=1 supersymmetric gauge theories determine whether they have a conformal fixed point in the IR. We systematically compute the Futaki invariants for a large family of 4d N=1 supersymmetric gauge t
Externí odkaz:
http://arxiv.org/abs/2410.18476
Autor:
Kim, Seong-Han, Kee, Chul-Sik
We propose new electromagnetic surface waves at the interface formed by connecting a perfect electric conductor (PEC) and a perfect magnetic conductor (PMC) parallel plate waveguides containing materials with positive permittivities and permeabilitie
Externí odkaz:
http://arxiv.org/abs/2410.17900