Zobrazeno 1 - 10
of 944
pro vyhledávání: '"Wong, Bryan"'
Autor:
Wu, Shixun, Ding, Yitong, Zhai, Yujia, Liu, Jinyang, Huang, Jiajun, Jian, Zizhe, Dai, Huangliang, Di, Sheng, Wong, Bryan M., Chen, Zizhong, Cappello, Franck
K-means is a widely used algorithm in clustering, however, its efficiency is primarily constrained by the computational cost of distance computing. Existing implementations suffer from suboptimal utilization of computational units and lack resilience
Externí odkaz:
http://arxiv.org/abs/2408.01391
Autor:
Wong, Bryan, Yi, Mun Yong
The classification of gigapixel-sized whole slide images (WSIs), digital representations of histological slides obtained via a high-resolution scanner, faces significant challenges associated with the meticulous and time-consuming nature of fine-grai
Externí odkaz:
http://arxiv.org/abs/2408.01162
Autor:
Wong, Bryan, Yi, Mun Yong
Multiple instance learning (MIL) has become a preferred method for classifying gigapixel whole slide images (WSIs), without requiring patch label annotation. The focus of the current MIL research stream is on the embedding-based MIL approach, which i
Externí odkaz:
http://arxiv.org/abs/2408.01167
Current histopathology research has primarily focused on using whole-slide images (WSIs) produced by scanners with weakly-supervised multiple instance learning (MIL). However, WSIs are costly, memory-intensive, and require extensive analysis time. As
Externí odkaz:
http://arxiv.org/abs/2407.21604
Recent advancements in graph neural networks (GNNs) and heterogeneous GNNs (HGNNs) have advanced node embeddings and relationship learning for various tasks. However, existing methods often rely on domain-specific predefined meta-paths, which are coa
Externí odkaz:
http://arxiv.org/abs/2407.20648
Autor:
Dieguez, Adrian Perez, Choi, Min, Okyay, Mahmut, Del Ben, Mauro, Wong, Bryan M., Ibrahim, Khaled Z.
Tuning searches are pivotal in High-Performance Computing (HPC), addressing complex optimization challenges in computational applications. The complexity arises not only from finely tuning parameters within routines but also potential interdependenci
Externí odkaz:
http://arxiv.org/abs/2403.08131
Publikováno v:
AVS Quantum Sci. 5, 043801 (2023)
We present a novel, computationally efficient approach to accelerate quantum optimal control calculations of large multi-qubit systems used in a variety of quantum computing applications. By leveraging the intrinsic symmetry of finite groups, the Hil
Externí odkaz:
http://arxiv.org/abs/2309.05884
Publikováno v:
J. Chem. Theory Comput., 19, 22, 7989-7997 (2024)
We present a new velocity-gauge real-time, time-dependent density functional tight-binding (VG-rtTDDFTB) implementation in the open-source DFTB+ software package (https://dftbplus.org) for probing electronic excitations in large, condensed matter sys
Externí odkaz:
http://arxiv.org/abs/2308.09782
Autor:
Wu, Shixun, Zhai, Yujia, Liu, Jinyang, Huang, Jiajun, Jian, Zizhe, Wong, Bryan M., Chen, Zizhong
General Matrix Multiplication (GEMM) is a crucial algorithm for various applications such as machine learning and scientific computing, and an efficient GEMM implementation is essential for the performance of these systems. While researchers often st
Externí odkaz:
http://arxiv.org/abs/2305.01024
Autor:
Jia Yi Fong, Francis1, Wei Zhi Wong, Bryan1, Si Pin Ong, Jamie1, Wei Zhong Tan, Beron2, Su-Fern Seng, Michaela3,4 michaela.seng@singhealth.com.sg, Ah Moy Tan3,4 tan.ah.moy01@singhealth.com.sg, Tanugroho, Raymond Reinaldo5
Publikováno v:
Annals of the Academy of Medicine, Singapore. Sep2024, Vol. 53 Issue 9, p530-538. 9p.