Zobrazeno 1 - 10
of 32 678
pro vyhledávání: '"P, Tsang"'
The fundamental problem with ultrasound-guided diagnosis is that the acquired images are often 2-D cross-sections of a 3-D anatomy, potentially missing important anatomical details. This limitation leads to challenges in ultrasound echocardiography,
Externí odkaz:
http://arxiv.org/abs/2409.09680
Autor:
Sazzad, A. B. M. R., Acharya, P., Back, P., Busenitz, J., Chernyak, D., Meng, Y., Piepke, A., Rhyne, C. A., Tsang, R.
This article describes a radon emanation measurement technique using liquid scintillator counting. A model for radon loading and transport is described, along with its calibration. Detector background and blank have been studied and quantified. The M
Externí odkaz:
http://arxiv.org/abs/2411.09384
Learning diverse and high-performance behaviors from a limited set of demonstrations is a grand challenge. Traditional imitation learning methods usually fail in this task because most of them are designed to learn one specific behavior even with mul
Externí odkaz:
http://arxiv.org/abs/2411.06965
Autor:
Vartanyan, David, Tsang, Benny T. H., Kasen, Daniel, Burrows, Adam, Wang, Tianshu, Teryosin, Lizzy
In order to better connect core-collapse supernovae (CCSN) theory with its observational signatures, we have developed a simulation pipeline from the onset of core collapse to beyond shock breakout. Using this framework, we present a three-dimensiona
Externí odkaz:
http://arxiv.org/abs/2411.03434
Worst-case fairness with off-the-shelf demographics achieves group parity by maximizing the model utility of the worst-off group. Nevertheless, demographic information is often unavailable in practical scenarios, which impedes the use of such a direc
Externí odkaz:
http://arxiv.org/abs/2411.03068
Due to privacy and security concerns, recent advancements in group fairness advocate for model training regardless of demographic information. However, most methods still require prior knowledge of demographics. In this study, we explore the potentia
Externí odkaz:
http://arxiv.org/abs/2411.02467
Autor:
Jia, Xiaojun, Gao, Sensen, Guo, Qing, Ma, Ke, Huang, Yihao, Qin, Simeng, Liu, Yang, Fellow, Ivor Tsang, Cao, Xiaochun
Vision-language pre-training (VLP) models excel at interpreting both images and text but remain vulnerable to multimodal adversarial examples (AEs). Advancing the generation of transferable AEs, which succeed across unseen models, is key to developin
Externí odkaz:
http://arxiv.org/abs/2411.02669
Autor:
Blum, T., Boyle, P. A., Bruno, M., Chakraborty, B., Erben, F., Gülpers, V., Hackl, A., Hermansson-Truedsson, N., Hill, R. C., Izubuchi, T., Jin, L., Jung, C., Lehner, C., McKeon, J., Meyer, A. S., Tomii, M., Tsang, J. T., Tuo, X. -Y.
We provide the first ab-initio calculation of the Euclidean long-distance window of the isospin symmetric light-quark connected contribution to the hadronic vacuum polarization for the muon $g-2$ and find $a_\mu^{\rm LD,iso,conn,ud} = 411.4(4.3)(2.4)
Externí odkaz:
http://arxiv.org/abs/2410.20590
Discovering user preferences across different domains is pivotal in cross-domain recommendation systems, particularly when platforms lack comprehensive user-item interactive data. The limited presence of shared users often hampers the effective model
Externí odkaz:
http://arxiv.org/abs/2410.20580
Chiral effective field theory ($\chi$EFT) has proved to be a powerful microscopic framework for predicting the properties of neutron-rich nuclear matter with quantified theoretical uncertainties up to about twice the nuclear saturation density. Tests
Externí odkaz:
http://arxiv.org/abs/2410.19971