Zobrazeno 1 - 10
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pro vyhledávání: '"Kao A"'
Publikováno v:
Clinical Ophthalmology, Vol Volume 16, Pp 2441-2451 (2022)
Gabriel Quesada,1 Daniel H Chang,2 Kevin L Waltz,3 Andrew A Kao,2 Rodrigo Quesada,1 Ying Wang,4 Leilei Ji,4 Dari Parizadeh,4 Luis Atiles4 1Grupo Oftalmo & Plastico, San Salvador, El Salvador; 2Empire Eye and Laser Center, Bakersfield, CA, USA; 3Centr
Externí odkaz:
https://doaj.org/article/c64e0e2532ed456d90366027536afa3a
Autor:
Jiang, Song, JU, Da, Cohen, Andrew, Mitts, Sasha, Foss, Aaron, Kao, Justine T, Li, Xian, Tian, Yuandong
How are LLM-based agents used in the future? While many of the existing work on agents has focused on improving the performance of a specific family of objective and challenging tasks, in this work, we take a different perspective by thinking about f
Externí odkaz:
http://arxiv.org/abs/2411.13904
Autor:
Kuo, Kao-Yueh, Ouyang, Yingkai
Erasures are the primary type of errors in physical systems dominated by leakage errors. While quantum error correction (QEC) using stabilizer codes can combat these error, the question of achieving near-capacity performance with explicit codes and e
Externí odkaz:
http://arxiv.org/abs/2411.13509
H5N1 highly pathogenic avian influenza (HPAI) has been recently circulating in previously unseen patterns. As the underlying causes are uncertain, we need a better understanding of the drivers of virus circulation, as they underpin the spread, and in
Externí odkaz:
http://arxiv.org/abs/2411.10424
Autor:
Hsieh, He-Yen, Li, Ziyun, Zhang, Sai Qian, Ting, Wei-Te Mark, Chang, Kao-Den, De Salvo, Barbara, Liu, Chiao, Kung, H. T.
We present GazeGen, a user interaction system that generates visual content (images and videos) for locations indicated by the user's eye gaze. GazeGen allows intuitive manipulation of visual content by targeting regions of interest with gaze. Using
Externí odkaz:
http://arxiv.org/abs/2411.04335
Autor:
Martinez, Gildardo, Siu, Justin, Dang, Steven, Gage, Dylan, Kao, Emma, Avila, Juan Carlos, You, Ruilin, McGorty, Ryan
Differential dynamic microscopy (DDM) typically relies on movies containing hundreds or thousands of frames to accurately quantify motion in soft matter systems. Using movies much shorter in duration produces noisier and less accurate results. This l
Externí odkaz:
http://arxiv.org/abs/2411.02314
Autor:
Nguyen, Daniel, Cohen, Myke C., Kao, Hsien-Te, Engberson, Grant, Penafiel, Louis, Lynch, Spencer, Volkova, Svitlana
As human-agent teaming (HAT) research continues to grow, computational methods for modeling HAT behaviors and measuring HAT effectiveness also continue to develop. One rising method involves the use of human digital twins (HDT) to approximate human b
Externí odkaz:
http://arxiv.org/abs/2411.01049
Autor:
Zhou, Hangyu, Kao, Chia-Hsiang, Phoo, Cheng Perng, Mall, Utkarsh, Hariharan, Bharath, Bala, Kavita
Clouds in satellite imagery pose a significant challenge for downstream applications. A major challenge in current cloud removal research is the absence of a comprehensive benchmark and a sufficiently large and diverse training dataset. To address th
Externí odkaz:
http://arxiv.org/abs/2410.23891
Autor:
Melendez, Alex Lee, Das, Shekhar, Rodriguez, Francisco Ayala, Kao, I-Hsuan, Liu, Wenhao, Williams, Archibald J., Lv, Bing, Goldberger, Joshua, Chatterjee, Shubhayu, Singh, Simranjeet, Hammel, P. Chris
Optical detection of magnetic resonance using quantum spin sensors (QSS) provides a spatially local and sensitive technique to probe spin dynamics in magnets. However, its utility as a probe of antiferromagnetic resonance (AFMR), wherein the characte
Externí odkaz:
http://arxiv.org/abs/2410.23421
Autor:
Battenberg, Eric, Skerry-Ryan, RJ, Stanton, Daisy, Mariooryad, Soroosh, Shannon, Matt, Salazar, Julian, Kao, David
Autoregressive (AR) Transformer-based sequence models are known to have difficulty generalizing to sequences longer than those seen during training. When applied to text-to-speech (TTS), these models tend to drop or repeat words or produce erratic ou
Externí odkaz:
http://arxiv.org/abs/2410.22179