Zobrazeno 1 - 10
of 2 459
pro vyhledávání: '"Wang, Eric A."'
Autor:
Wiley, James, Brown, Aaron, Kupke, Renate, Cosens, Maren, Wright, Shelley A., Maire, Jerome, Magnone, Kenneth, Kress, Evan, Wang, Eric, Johnson, Chris, Larkin, James E., Fitzgerald, Michael P., Kassis, Marc, Jones, Tucker
Publikováno v:
Proc. SPIE 13096, Ground-based and Airborne Instrumentation for Astronomy X, 130967B (18 July 2024)
Liger is an adaptive optics (AO) fed imager and integral field spectrograph (IFS) designed to take advantage of the Keck All-sky Precision Adaptive-optics (KAPA) upgrade to the Keck I telescope. Liger adapts the design of the InfraRed Imaging Spectro
Externí odkaz:
http://arxiv.org/abs/2409.16263
Autor:
Turishcheva, Polina, Fahey, Paul G., Vystrčilová, Michaela, Hansel, Laura, Froebe, Rachel, Ponder, Kayla, Qiu, Yongrong, Willeke, Konstantin F., Bashiri, Mohammad, Baikulov, Ruslan, Zhu, Yu, Ma, Lei, Yu, Shan, Huang, Tiejun, Li, Bryan M., De Wulf, Wolf, Kudryashova, Nina, Hennig, Matthias H., Rochefort, Nathalie L., Onken, Arno, Wang, Eric, Ding, Zhiwei, Tolias, Andreas S., Sinz, Fabian H., Ecker, Alexander S
Understanding how biological visual systems process information is challenging because of the nonlinear relationship between visual input and neuronal responses. Artificial neural networks allow computational neuroscientists to create predictive mode
Externí odkaz:
http://arxiv.org/abs/2407.09100
Autor:
Chen, Zhichao, Li, Haoxuan, Wang, Fangyikang, Zhang, Odin, Xu, Hu, Jiang, Xiaoyu, Song, Zhihuan, Wang, Eric H.
Diffusion models (DMs) have gained attention in Missing Data Imputation (MDI), but there remain two long-neglected issues to be addressed: (1). Inaccurate Imputation, which arises from inherently sample-diversification-pursuing generative process of
Externí odkaz:
http://arxiv.org/abs/2406.15762
Autor:
Chaves, Juan Manuel Zambrano, Wang, Eric, Tu, Tao, Vaishnav, Eeshit Dhaval, Lee, Byron, Mahdavi, S. Sara, Semturs, Christopher, Fleet, David, Natarajan, Vivek, Azizi, Shekoofeh
Developing therapeutics is a lengthy and expensive process that requires the satisfaction of many different criteria, and AI models capable of expediting the process would be invaluable. However, the majority of current AI approaches address only a n
Externí odkaz:
http://arxiv.org/abs/2406.06316
Autor:
Ahmed, Kareem, Teso, Stefano, Morettin, Paolo, Di Liello, Luca, Ardino, Pierfrancesco, Gobbi, Jacopo, Liang, Yitao, Wang, Eric, Chang, Kai-Wei, Passerini, Andrea, Broeck, Guy Van den
Structured output prediction problems are ubiquitous in machine learning. The prominent approach leverages neural networks as powerful feature extractors, otherwise assuming the independence of the outputs. These outputs, however, jointly encode an o
Externí odkaz:
http://arxiv.org/abs/2405.07387
Autor:
Yang, Lin, Xu, Shawn, Sellergren, Andrew, Kohlberger, Timo, Zhou, Yuchen, Ktena, Ira, Kiraly, Atilla, Ahmed, Faruk, Hormozdiari, Farhad, Jaroensri, Tiam, Wang, Eric, Wulczyn, Ellery, Jamil, Fayaz, Guidroz, Theo, Lau, Chuck, Qiao, Siyuan, Liu, Yun, Goel, Akshay, Park, Kendall, Agharwal, Arnav, George, Nick, Wang, Yang, Tanno, Ryutaro, Barrett, David G. T., Weng, Wei-Hung, Mahdavi, S. Sara, Saab, Khaled, Tu, Tao, Kalidindi, Sreenivasa Raju, Etemadi, Mozziyar, Cuadros, Jorge, Sorensen, Gregory, Matias, Yossi, Chou, Katherine, Corrado, Greg, Barral, Joelle, Shetty, Shravya, Fleet, David, Eslami, S. M. Ali, Tse, Daniel, Prabhakara, Shruthi, McLean, Cory, Steiner, Dave, Pilgrim, Rory, Kelly, Christopher, Azizi, Shekoofeh, Golden, Daniel
Many clinical tasks require an understanding of specialized data, such as medical images and genomics, which is not typically found in general-purpose large multimodal models. Building upon Gemini's multimodal models, we develop several models within
Externí odkaz:
http://arxiv.org/abs/2405.03162
In this paper, we explore the challenges of ensuring security and privacy for users from diverse demographic backgrounds. We propose a threat modeling approach to identify potential risks and countermeasures for product inclusion in security and priv
Externí odkaz:
http://arxiv.org/abs/2404.13220
Scientific machine learning (SciML) has emerged as a versatile approach to address complex computational science and engineering problems. Within this field, physics-informed neural networks (PINNs) and deep operator networks (DeepONets) stand out as
Externí odkaz:
http://arxiv.org/abs/2401.16645
Autor:
Dainotti, Maria Giovanna, Taira, Elias, Wang, Eric, Lehman, Elias, Narendra, Aditya, Pollo, Agnieszka, Madejski, Grzegorz M., Petrosian, Vahe, Bogdan, Malgorzata, Dey, Apratim, Bhardwaj, Shubham
Gamma-Ray Bursts (GRBs), due to their high luminosities are detected up to redshift 10, and thus have the potential to be vital cosmological probes of early processes in the universe. Fulfilling this potential requires a large sample of GRBs with kno
Externí odkaz:
http://arxiv.org/abs/2401.03589
Autor:
Konopacky, Quinn M., Baker, Ashley D., Mawet, Dimitri, Fitzgerald, Michael P., Jovanovic, Nemanja, Beichman, Charles, Ruane, Garreth, Bertz, Rob, Terada, Hiroshi, Dekany, Richard, Lingvay, Larry, Kassis, Marc, Anderson, David, Tamura, Motohide, Benneke, Bjorn, Beatty, Thomas, Do, Tuan, Nishiyama, Shogo, Plavchan, Peter, Wang, Jason, Wang, Ji, Burgasser, Adam, Ruffio, Jean-Baptiste, Zhang, Huihao, Brown, Aaron, Fucik, Jason, Gibbs, Aidan, Gibson, Rose, Halverson, Sam, Johnson, Christopher, Karkar, Sonia, Kotani, Takayuki, Kress, Evan, Leifer, Stephanie, Magnone, Kenneth, Maire, Jerome, Pahuja, Rishi, Porter, Michael, Roberts, Mitsuko, Sappey, Ben, Thorne, Jim, Wang, Eric, Artigau, Etienne, Blake, Geoffrey A., Canalizo, Gabriela, Chen, Guo, Doppmann, Greg, Doyon, Rene, Dressing, Courtney, Fang, Min, Greene, Thomas, Herczeg, Greg, Hillenbrand, Lynne, Howard, Andrew, Kane, Stephen, Kataria, Tiffany, Kempton, Eliza, Knutson, Heather, Lafreniere, David, Liu, Chao, Metchev, Stanimir, Millar-Blanchaer, Max, Narita, Norio, Pandey, Gajendra, Rajaguru, S. P., Robertson, Paul, Salyk, Colette, Sato, Bunei, Schlawin, Evertt, Sengupta, Sujan, Sivarani, Thirupathi, Skidmore, Warren, Vasisht, Gautam, Yasui, Chikako, Zhang, Hui
HISPEC is a new, high-resolution near-infrared spectrograph being designed for the W.M. Keck II telescope. By offering single-shot, R=100,000 between 0.98 - 2.5 um, HISPEC will enable spectroscopy of transiting and non-transiting exoplanets in close
Externí odkaz:
http://arxiv.org/abs/2309.11050