Zobrazeno 1 - 10
of 20 359
pro vyhledávání: '"Lee, An Yong"'
Autor:
Lee, Dohyeon, Lee, Hyun-Seung, Lee, Moosung, Kang, Minhee, Kim, Geon, Kim, Tae Yeul, Lee, Nam Yong, Park, YongKeun
Bacterial heterogeneity is pivotal for adaptation to diverse environments, posing significant challenges in microbial diagnostics and therapeutic interventions. Recent advancements in high-resolution optical microscopy have revolutionized our ability
Externí odkaz:
http://arxiv.org/abs/2501.01592
Autor:
Kim, Sunwoo, Lee, Soo Yong, Bu, Fanchen, Kang, Shinhwan, Kim, Kyungho, Yoo, Jaemin, Shin, Kijung
Graph autoencoders (Graph-AEs) learn representations of given graphs by aiming to accurately reconstruct them. A notable application of Graph-AEs is graph-level anomaly detection (GLAD), whose objective is to identify graphs with anomalous topologica
Externí odkaz:
http://arxiv.org/abs/2410.20366
The goal of this paper is to encode a 3D scene into an extremely compact representation from 2D images and to enable its transmittance, decoding and rendering in real-time across various platforms. Despite the progress in NeRFs and Gaussian Splats, t
Externí odkaz:
http://arxiv.org/abs/2409.15689
Autor:
Lee, Jae Yong, Kim, Yeoneung
The framework of deep operator network (DeepONet) has been widely exploited thanks to its capability of solving high dimensional partial differential equations. In this paper, we incorporate DeepONet with a recently developed policy iteration scheme
Externí odkaz:
http://arxiv.org/abs/2406.10920
Microwave quantum illumination with entangled pairs of microwave signal and optical idler modes, can achieve the sub-optimal performance with joint measurement of the signal and idler modes. Here, we first propose a testbed of microwave quantum illum
Externí odkaz:
http://arxiv.org/abs/2405.14118
Combinatorial optimization (CO) is naturally discrete, making machine learning based on differentiable optimization inapplicable. Karalias & Loukas (2020) adapted the probabilistic method to incorporate CO into differentiable optimization. Their work
Externí odkaz:
http://arxiv.org/abs/2405.08424
Large Language Models (LLMs) have dramatically advanced AI applications, yet their deployment remains challenging due to their immense inference costs. Recent studies ameliorate the computational costs of LLMs by increasing their activation sparsity
Externí odkaz:
http://arxiv.org/abs/2404.08763
The latest regularized Neural Radiance Field (NeRF) approaches produce poor geometry and view extrapolation for large scale sparse view scenes, such as ETH3D. Density-based approaches tend to be under-constrained, while surface-based approaches tend
Externí odkaz:
http://arxiv.org/abs/2404.08252
Higher-order interactions (HOIs) are ubiquitous in real-world complex systems and applications. Investigation of deep learning for HOIs, thus, has become a valuable agenda for the data mining and machine learning communities. As networks of HOIs are
Externí odkaz:
http://arxiv.org/abs/2404.01039
Hypergraphs are marked by complex topology, expressing higher-order interactions among multiple nodes with hyperedges, and better capturing the topology is essential for effective representation learning. Recent advances in generative self-supervised
Externí odkaz:
http://arxiv.org/abs/2404.00638