Zobrazeno 1 - 10
of 745
pro vyhledávání: '"Krass, P."'
Autor:
Krass, Marc-Dominik, Prumbaum, Nils, Pachlatko, Raphael, Degen, Christian L., Eichler, Alexander
Magnetic Resonance Force Microscopy (MRFM) describes a range of approaches to detect nuclear spins with mechanical sensors. MRFM has the potential to enable magnetic resonance imaging (MRI) with near-atomic spatial resolution, opening up exciting pos
Externí odkaz:
http://arxiv.org/abs/2408.06775
In this paper, we apply a supervised machine-learning approach to solve a fundamental problem in queueing theory: estimating the transient distribution of the number in the system for a G(t)/GI/1. We develop a neural network mechanism that provides a
Externí odkaz:
http://arxiv.org/abs/2407.08765
Autor:
Pachlatko, Raphael, Prumbaum, Nils, Krass, Marc-Dominik, Grob, Urs, Degen, Christian L., Eichler, Alexander
Publikováno v:
Nano Letters 24, 2081 (2024)
Nanoscale magnetic resonance imaging (NanoMRI) is an active area of applied research with potential use in structural biology and quantum engineering. The success of this technological vision hinges on improving the instrument's sensitivity and funct
Externí odkaz:
http://arxiv.org/abs/2312.04129
Autor:
Feras Jirjees, Sanah Hasan, Ines Krass, Ward Saidawi, Mohammed Khalid Al-Juboori, Amna M. Othman, Karem H. Alzoubi, Hamzah Alzubaidi
Publikováno v:
BMC Public Health, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Meaningful communication between health service users and providers is essential. However, when stakeholders are unfamiliar with new health services, innovative communication methods are necessary to engage them. The aim of the study was to
Externí odkaz:
https://doaj.org/article/ac9af555bfee45f2bd086bf2286fb719
Autor:
Chapela-Campa, David, Benchekroun, Ismail, Baron, Opher, Dumas, Marlon, Krass, Dmitry, Senderovich, Arik
Business Process Simulation (BPS) is an approach to analyze the performance of business processes under different scenarios. For example, BPS allows us to estimate what would be the cycle time of a process if one or more resources became unavailable.
Externí odkaz:
http://arxiv.org/abs/2303.17463
Autor:
Henderson, Peter, Krass, Mark S., Zheng, Lucia, Guha, Neel, Manning, Christopher D., Jurafsky, Dan, Ho, Daniel E.
One concern with the rise of large language models lies with their potential for significant harm, particularly from pretraining on biased, obscene, copyrighted, and private information. Emerging ethical approaches have attempted to filter pretrainin
Externí odkaz:
http://arxiv.org/abs/2207.00220
Autor:
Krass, Marc-Dominik, Prumbaum, Nils, Pachlatko, Raphael, Grob, Urs, Takahashi, Hiroki, Yamauchi, Yohei, Degen, Christian L., Eichler, Alexander
Publikováno v:
Phys. Rev. Applied 18, 034052 (2022)
Long and thin scanning force cantilevers are sensitive to small forces, but also vulnerable to detrimental non-contact interactions. Here we present an experiment with a cantilever whose spring constant and static deflection are dominated by the inte
Externí odkaz:
http://arxiv.org/abs/2206.03168
In this paper, we analyze how well a machine can solve a general problem in queueing theory. To answer this question, we use a deep learning model to predict the stationary queue-length distribution of an $M/G/1$ queue (Poisson arrivals, general serv
Externí odkaz:
http://arxiv.org/abs/2202.01729
Autor:
Ines Krass, Michael J. Twigg, Bernadette Mitchell, Frances Wilson, Mohammadreza Mohebbi, Peta Trinder, Sophy T. F. Shih, Rob Carter, Vincent L. Versace, Kevin McNamara
Publikováno v:
BMC Health Services Research, Vol 23, Iss 1, Pp 1-13 (2023)
Abstract Background The Pharmacy Diabetes Screening Trial (PDST) evaluated three approaches to screening for undiagnosed type 2 diabetes mellitus (T2DM) in community pharmacy: (1) paper-based risk assessment (AUSDRISK) alone; and AUSDRISK followed by
Externí odkaz:
https://doaj.org/article/0b972575932f434d9795a86185a2dbfe
Autor:
Bommasani, Rishi, Hudson, Drew A., Adeli, Ehsan, Altman, Russ, Arora, Simran, von Arx, Sydney, Bernstein, Michael S., Bohg, Jeannette, Bosselut, Antoine, Brunskill, Emma, Brynjolfsson, Erik, Buch, Shyamal, Card, Dallas, Castellon, Rodrigo, Chatterji, Niladri, Chen, Annie, Creel, Kathleen, Davis, Jared Quincy, Demszky, Dora, Donahue, Chris, Doumbouya, Moussa, Durmus, Esin, Ermon, Stefano, Etchemendy, John, Ethayarajh, Kawin, Fei-Fei, Li, Finn, Chelsea, Gale, Trevor, Gillespie, Lauren, Goel, Karan, Goodman, Noah, Grossman, Shelby, Guha, Neel, Hashimoto, Tatsunori, Henderson, Peter, Hewitt, John, Ho, Daniel E., Hong, Jenny, Hsu, Kyle, Huang, Jing, Icard, Thomas, Jain, Saahil, Jurafsky, Dan, Kalluri, Pratyusha, Karamcheti, Siddharth, Keeling, Geoff, Khani, Fereshte, Khattab, Omar, Koh, Pang Wei, Krass, Mark, Krishna, Ranjay, Kuditipudi, Rohith, Kumar, Ananya, Ladhak, Faisal, Lee, Mina, Lee, Tony, Leskovec, Jure, Levent, Isabelle, Li, Xiang Lisa, Li, Xuechen, Ma, Tengyu, Malik, Ali, Manning, Christopher D., Mirchandani, Suvir, Mitchell, Eric, Munyikwa, Zanele, Nair, Suraj, Narayan, Avanika, Narayanan, Deepak, Newman, Ben, Nie, Allen, Niebles, Juan Carlos, Nilforoshan, Hamed, Nyarko, Julian, Ogut, Giray, Orr, Laurel, Papadimitriou, Isabel, Park, Joon Sung, Piech, Chris, Portelance, Eva, Potts, Christopher, Raghunathan, Aditi, Reich, Rob, Ren, Hongyu, Rong, Frieda, Roohani, Yusuf, Ruiz, Camilo, Ryan, Jack, Ré, Christopher, Sadigh, Dorsa, Sagawa, Shiori, Santhanam, Keshav, Shih, Andy, Srinivasan, Krishnan, Tamkin, Alex, Taori, Rohan, Thomas, Armin W., Tramèr, Florian, Wang, Rose E., Wang, William, Wu, Bohan, Wu, Jiajun, Wu, Yuhuai, Xie, Sang Michael, Yasunaga, Michihiro, You, Jiaxuan, Zaharia, Matei, Zhang, Michael, Zhang, Tianyi, Zhang, Xikun, Zhang, Yuhui, Zheng, Lucia, Zhou, Kaitlyn, Liang, Percy
AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks. We call these models foundation models to underscore their critically
Externí odkaz:
http://arxiv.org/abs/2108.07258