Zobrazeno 1 - 10
of 527
pro vyhledávání: '"Park, JaeWoo"'
Autor:
Park, Jaewoo
The molten salt reactor (MSR) is one of the advanced nuclear reactors expected to be alternatives to the conventional water-cooled nuclear reactor systems. Despite many advantages of MSRs, properties of molten salts have not been sufficiently measure
Externí odkaz:
https://hdl.handle.net/10919/118633
In anomaly detection, the scarcity of anomalous data compared to normal data poses a challenge in effectively utilizing deep neural network representations to identify anomalous features. From a data-centric perspective, generative models can solve t
Externí odkaz:
http://arxiv.org/abs/2411.16767
Bayesian inference for doubly intractable distributions is challenging because they include intractable terms, which are functions of parameters of interest. Although several alternatives have been developed for such models, they are computationally
Externí odkaz:
http://arxiv.org/abs/2410.21021
Autor:
Jeong, Dayena, Park, Jaewoo, Jo, Jeonghee, Park, Jongkil, Kim, Jaewook, Jang, Hyun Jae, Lee, Suyoun, Park, Seongsik
Recent deep neural networks (DNNs), such as diffusion models [1], have faced high computational demands. Thus, spiking neural networks (SNNs) have attracted lots of attention as energy-efficient neural networks. However, conventional spiking neurons,
Externí odkaz:
http://arxiv.org/abs/2409.00044
Autor:
Jung, Yoon Gyo, Park, Jaewoo, Dong, Xingbo, Park, Hojin, Teoh, Andrew Beng Jin, Camps, Octavia
Understanding the vulnerability of face recognition systems to malicious attacks is of critical importance. Previous works have focused on reconstructing face images that can penetrate a targeted verification system. Even in the white-box scenario, h
Externí odkaz:
http://arxiv.org/abs/2407.02403
We show the first near-linear time randomized algorithms for listing all minimum vertex cuts of polylogarithmic size that separate the graph into at least three connected components (also known as shredders) and for finding the most shattering one, i
Externí odkaz:
http://arxiv.org/abs/2405.03801
Deep learning models continue to advance in accuracy, yet they remain vulnerable to adversarial attacks, which often lead to the misclassification of adversarial examples. Adversarial training is used to mitigate this problem by increasing robustness
Externí odkaz:
http://arxiv.org/abs/2402.12187
Accurately estimating the pose of an object is a crucial task in computer vision and robotics. There are two main deep learning approaches for this: geometric representation regression and iterative refinement. However, these methods have some limita
Externí odkaz:
http://arxiv.org/abs/2401.16284
Spatial functional data arise in many settings, such as particulate matter curves observed at monitoring stations and age population curves at each areal unit. Most existing functional regression models have limited applicability because they do not
Externí odkaz:
http://arxiv.org/abs/2401.08175
Recently DRAM-based PIMs (processing-in-memories) with unmodified cell arrays have demonstrated impressive performance for accelerating AI applications. However, due to the very restrictive hardware constraints, PIM remains an accelerator for simple
Externí odkaz:
http://arxiv.org/abs/2310.09715