Zobrazeno 1 - 10
of 63 089
pro vyhledávání: '"A. Hsueh"'
Autor:
Bastl, Stefan, Burke, Rhuaidi, Chatterjee, Rima, Dey, Subhankar, Durst, Alison, Friedl, Stefan, Galvin, Daniel, Rivas, Alejandro García, Hirsch, Tobias, Hobohm, Cara, Hsueh, Chun-Sheng, Kegel, Marc, Kern, Frieda, Lee, Shun Ming Samuel, Löh, Clara, Manikandan, Naageswaran, Mousseau, Léo, Munser, Lars, Pencovitch, Mark, Perras, Patrick, Powell, Mark, Quintanilha, José Pedro, Schambeck, Lisa, Suchodoll, David, Tancer, Martin, Thiele, Annika, Truöl, Paula, Uschold, Matthias, Veselá, Simona, Weiß, Melvin, von Wunsch-Rolshoven, Magdalina
We show that there exists an algorithm that takes as input two closed, simply connected, topological 4-manifolds and decides whether or not these 4-manifolds are homeomorphic. In particular, we explain in detail how closed, simply connected, topologi
Externí odkaz:
http://arxiv.org/abs/2411.08775
Our work explores the utilization of deep learning, specifically leveraging the CodeBERT model, to enhance code security testing for Python applications by detecting SQL injection vulnerabilities. Unlike traditional security testing methods that may
Externí odkaz:
http://arxiv.org/abs/2410.21968
We introduce a novel adaptive eigenvalue filtering strategy to stabilize and accelerate the optimization of Neo-Hookean energy and its variants under the Projected Newton framework. For the first time, we show that Newton's method, Projected Newton w
Externí odkaz:
http://arxiv.org/abs/2410.10102
This paper introduces a fast and robust method for simplifying surface triangle meshes in the wild while maintaining high visual quality. While previous methods achieve excellent results on manifold meshes by using the quadric error metric, they suff
Externí odkaz:
http://arxiv.org/abs/2409.15458
Autor:
Chen, Yi-Hsun, Lo, Ping-Yuan, Boschen, Kyle W., Peng, Guan-Hao, Huang, Chun-Jui, Holtzman, Luke N., Hsu, Chih-En, Hsu, Yung-Ning, Holbrook, Madisen, Wang, Wei-Hua, Barmak, Katayun, Hone, James, Hawrylak, Pawel, Hsueh, Hung-Chung, Davis, Jeffrey A., Cheng, Shun-Jen, Fuhrer, Michael S., Chen, Shao-Yu
In this work, we report a pronounced light upconversion in few-layer transition metal dichalcogenides. Our joint theory-experiment study attributes the upconversion photoluminescence to a resonant exciton-exciton annihilation involving a pair of dark
Externí odkaz:
http://arxiv.org/abs/2409.03387
Autor:
Chaudhury, Sumilak, Johnson, Karl, Gao, Chengkuan, Lin, Bill, Fainman, Yeshaiahu, Hsueh, Tzu-Chien
An energy/area-efficient low-cost broadband linearity enhancement technique for electro-optic micro-ring modulators (MRM) is proposed to achieve 6.1-dB dynamic linearity improvement in spurious-free-dynamic-range with intermodulation distortions (IMD
Externí odkaz:
http://arxiv.org/abs/2407.11172
Autor:
Liu, Hsueh-Ti Derek, Agrawala, Maneesh, Yuksel, Cem, Omernick, Tim, Misra, Vinith, Corazza, Stefano, McGuire, Morgan, Zordan, Victor
This paper presents a unified differentiable boolean operator for implicit solid shape modeling using Constructive Solid Geometry (CSG). Traditional CSG relies on min, max operators to perform boolean operations on implicit shapes. But because these
Externí odkaz:
http://arxiv.org/abs/2407.10954
Autor:
Nuha, Ulin, Lin, Chih-Hsueh
Several machine learning schemes have attempted to perform the detection of spam messages. However, those schemes mostly require a huge amount of labeled data. The existing techniques addressing the lack of data availability have issues with effectiv
Externí odkaz:
http://arxiv.org/abs/2407.04990
Vector fields are widely used to represent and model flows for many science and engineering applications. This paper introduces a novel neural network architecture for learning tangent vector fields that are intrinsically defined on manifold surfaces
Externí odkaz:
http://arxiv.org/abs/2406.09648
Autor:
McAreavey, Kevin, Liu, Weiru, Bauters, Kim, Ivory, Dennis, Loukas, George, Panaousis, Manos, Chen, Hsueh-Ju, Gill, Rea, Payler, Rachael, Vasalou, Asimina
In this paper we present results from a qualitative field study on explainable AI (XAI) for lay users (n = 18) who were subjected to AI cyberattacks. The study was based on a custom-built smart heating application called Squid and was conducted over
Externí odkaz:
http://arxiv.org/abs/2406.07369