Zobrazeno 61 - 70
of 654 910
pro vyhledávání: '"Campbell A"'
Autor:
Gallardo MJ, Sarkisian SR Jr, Vold SD, Singh IP, Flowers BE, Campbell A, Dhamdhere K, Samuelson TW
Publikováno v:
Clinical Ophthalmology, Vol Volume 15, Pp 481-489 (2021)
Mark J Gallardo,1 Steven R Sarkisian Jr,2 Steven D Vold,3 Inder Paul Singh,4 Brian E Flowers,5 Anita Campbell,6 Kavita Dhamdhere,7 Thomas W Samuelson8 On behalf of the GEMINI study group1El Paso Eye Surgeons, PA, El Paso, TX, USA; 2Oklahoma Eye Surge
Externí odkaz:
https://doaj.org/article/885e80e612134cb28df3267d472d6a23
Publikováno v:
Food and Environment Safety, Vol 19, Iss 4, Pp 307-315 (2020)
The purpose of this paper is to produce and optimize brix from cassava peels for bioethanol production using Saccharomyces cerevisiae. The use of agricultural waste products in bioethanol production helps in decreasing reliance on food crops. Optimiz
Externí odkaz:
https://doaj.org/article/9b1236e493c34895ae7714d7ece1c1ad
Autor:
Gonzales, Alvin, Herrman, Rebekah, Campbell, Colin, Gaidai, Igor, Liu, Ji, Tomesh, Teague, Saleem, Zain H.
Continuous-time quantum walks (CTQWs) on dynamic graphs, referred to as dynamic CTQWs, are a recently introduced universal model of computation that offers a new paradigm in which to envision quantum algorithms. In this work we develop a mapping from
Externí odkaz:
http://arxiv.org/abs/2405.20273
Autor:
Marjieh, Raja, Kumar, Sreejan, Campbell, Declan, Zhang, Liyi, Bencomo, Gianluca, Snell, Jake, Griffiths, Thomas L.
Humans rely on strong inductive biases to learn from few examples and abstract useful information from sensory data. Instilling such biases in machine learning models has been shown to improve their performance on various benchmarks including few-sho
Externí odkaz:
http://arxiv.org/abs/2405.19420
We investigate the feasibility of deploying reinforcement learning (RL) policies for constrained crowd navigation using a low-fidelity simulator. We introduce a representation of the dynamic environment, separating human and obstacle representations.
Externí odkaz:
http://arxiv.org/abs/2405.16830
Autor:
Chen, Xiangyu, Liu, Zhenzhen, Luo, Katie Z, Datta, Siddhartha, Polavaram, Adhitya, Wang, Yan, You, Yurong, Li, Boyi, Pavone, Marco, Chao, Wei-Lun, Campbell, Mark, Hariharan, Bharath, Weinberger, Kilian Q.
Ensuring robust 3D object detection and localization is crucial for many applications in robotics and autonomous driving. Recent models, however, face difficulties in maintaining high performance when applied to domains with differing sensor setups o
Externí odkaz:
http://arxiv.org/abs/2405.16034
Floquet codes are an intriguing generalisation of stabiliser and subsystem codes, which can provide good fault-tolerant characteristics while benefiting from reduced connectivity requirements in hardware. A recent question of interest has been how to
Externí odkaz:
http://arxiv.org/abs/2405.15854
Autor:
Jones, Eric B., Winkleblack, Cody James, Campbell, Colin, Rotello, Caleb, Dahl, Edward D., Reynolds, Matthew, Graf, Peter, Jones, Wesley
We present a hardware-reconfigurable ansatz on $N_q$-qubits for the variational preparation of many-body states of the Anderson impurity model (AIM) with $N_{\text{imp}}+N_{\text{bath}}=N_q/2$ sites, which conserves total charge and spin z-component
Externí odkaz:
http://arxiv.org/abs/2405.15069
Autor:
Rawles, Christopher, Clinckemaillie, Sarah, Chang, Yifan, Waltz, Jonathan, Lau, Gabrielle, Fair, Marybeth, Li, Alice, Bishop, William, Li, Wei, Campbell-Ajala, Folawiyo, Toyama, Daniel, Berry, Robert, Tyamagundlu, Divya, Lillicrap, Timothy, Riva, Oriana
Autonomous agents that execute human tasks by controlling computers can enhance human productivity and application accessibility. However, progress in this field will be driven by realistic and reproducible benchmarks. We present AndroidWorld, a full
Externí odkaz:
http://arxiv.org/abs/2405.14573
Autor:
Schmidt, Lena, Hair, Kaitlyn, Graziozi, Sergio, Campbell, Fiona, Kapp, Claudia, Khanteymoori, Alireza, Craig, Dawn, Engelbert, Mark, Thomas, James
Publikováno v:
Proceedings of the 3rd Workshop on Augmented Intelligence for Technology-Assisted Reviews Systems, 2024
This paper describes a rapid feasibility study of using GPT-4, a large language model (LLM), to (semi)automate data extraction in systematic reviews. Despite the recent surge of interest in LLMs there is still a lack of understanding of how to design
Externí odkaz:
http://arxiv.org/abs/2405.14445