Zobrazeno 1 - 10
of 11 668
pro vyhledávání: '"ZHANG, Shuo"'
Knowledge distillation (KD) has been widely studied in unsupervised Industrial Image Anomaly Detection (AD), but its application to unsupervised multimodal AD remains underexplored. Existing KD-based methods for multimodal AD that use fused multimoda
Externí odkaz:
http://arxiv.org/abs/2412.08949
Knowledge Distillation (KD) is a promising approach for unsupervised Anomaly Detection (AD). However, the student network's over-generalization often diminishes the crucial representation differences between teacher and student in anomalous regions,
Externí odkaz:
http://arxiv.org/abs/2412.07579
Autor:
Zhang, Shuo
Finite element spaces by Whitney $k$-forms on cubical meshes in $\mathbb{R}^n$ are presented. Based on the spaces, compatible discretizations to $H\Lambda^k$ problems are provided, and discrete de Rham complexes and commutative diagrams are construct
Externí odkaz:
http://arxiv.org/abs/2412.07118
In this work, we demonstrate the integration of a score-matching diffusion model into a deterministic architecture for time-domain musical source extraction, resulting in enhanced audio quality. To address the typically slow iterative sampling proces
Externí odkaz:
http://arxiv.org/abs/2412.06965
Autor:
Sun, Shenglan, Wang, Fei, Zhang, Huawei, Xue, Xiang-Xiang, Huang, Yang, Zhang, Ruizhi, Rix, Hans-Walter, Li, Xinyi, Liu, Gaochao, Zhang, Lan, Yang, Chengqun, Zhang, Shuo
Motivated by the vast gap between photometric and spectroscopic data volumes, there is great potential in using 5D kinematic information to identify and study substructures of the Milky Way. We identify substructures in the Galactic halo using 46,575
Externí odkaz:
http://arxiv.org/abs/2411.13122
Autor:
Zhang, Shuo, Liu, Jian K.
Protein language models (PLMs) are capable of learning the relationships between protein sequences and functions by treating amino acid sequences as textual data in a self-supervised manner. However, fine-tuning these models typically demands substan
Externí odkaz:
http://arxiv.org/abs/2411.11530
Autor:
Kim, Chanho, Park, Jaegeun, An, Hongjun, Mori, Kaya, Reynolds, Stephen P., Safi-Harb, Samar, Zhang, Shuo
We present a detailed X-ray investigation of a region (S1) exhibiting non-thermal X-ray emission within the supernova remnant (SNR) CTB 37B hosting the magnetar CXOU J171405.7$-$381031. Previous analyses modeled this emission with a power law (PL), i
Externí odkaz:
http://arxiv.org/abs/2411.09902
Autor:
Yu, Haijun, Zhang, Shuo
Deep neural network approaches show promise in solving partial differential equations. However, unlike traditional numerical methods, they face challenges in enforcing essential boundary conditions. The widely adopted penalty-type methods, for exampl
Externí odkaz:
http://arxiv.org/abs/2411.09898
While tangible user interface has shown its power in naturally interacting with rigid or soft objects, users cannot conveniently use different types of granular materials as the interaction media. We introduce DipMe as a smart device to recognize the
Externí odkaz:
http://arxiv.org/abs/2411.08641
Data cleaning is a crucial yet challenging task in data analysis, often requiring significant manual effort. To automate data cleaning, previous systems have relied on statistical rules derived from erroneous data, resulting in low accuracy and recal
Externí odkaz:
http://arxiv.org/abs/2410.15547