Zobrazeno 1 - 10
of 4 462
pro vyhledávání: '"Lee, John P."'
In this study, we introduce FEET, a standardized protocol designed to guide the development and benchmarking of foundation models. While numerous benchmark datasets exist for evaluating these models, we propose a structured evaluation protocol across
Externí odkaz:
http://arxiv.org/abs/2411.01322
Autor:
Chocan, Macarena S., Wuyckens, Sophie, Dasnoy, Damien, Di Perri, Dario, Villarruel, Elena Borderias, Engwall, Erik, Lee, John A., Barragán-Montero, Ana M., Sterpin, Edmond
Background and purpose: IMPT faces challenges in lung cancer treatment, like maintaining plan robustness for moving tumors against setup, range errors, and interplay effects. Proton Arc Therapy (PAT) is an alternative to maintain target coverage, pot
Externí odkaz:
http://arxiv.org/abs/2409.16982
Accurately modeling the dynamics of high-density ratio ($\mathcal{O}(10^5)$) two-phase flows is important for many applications in material science and manufacturing. In this work, we consider numerical simulations of molten metal undergoing microgra
Externí odkaz:
http://arxiv.org/abs/2406.17933
Autor:
Zhong, Xinzhi, Zhou, Yang, Kamaraj, Varshini, Zhou, Zhenhao, Kontar, Wissam, Negrut, Dan, Lee, John D., Ahn, Soyoung
This paper develops a novel car-following control method to reduce voluntary driver interventions and improve traffic stability in Automated Vehicles (AVs). Through a combination of experimental and empirical analysis, we show how voluntary driver in
Externí odkaz:
http://arxiv.org/abs/2404.05832
Autor:
Lee, Jonathan W., Wang, Han, Jang, Kathy, Hayat, Amaury, Bunting, Matthew, Alanqary, Arwa, Barbour, William, Fu, Zhe, Gong, Xiaoqian, Gunter, George, Hornstein, Sharon, Kreidieh, Abdul Rahman, Lichtlé, Nathan, Nice, Matthew W., Richardson, William A., Shah, Adit, Vinitsky, Eugene, Wu, Fangyu, Xiang, Shengquan, Almatrudi, Sulaiman, Althukair, Fahd, Bhadani, Rahul, Carpio, Joy, Chekroun, Raphael, Cheng, Eric, Chiri, Maria Teresa, Chou, Fang-Chieh, Delorenzo, Ryan, Gibson, Marsalis, Gloudemans, Derek, Gollakota, Anish, Ji, Junyi, Keimer, Alexander, Khoudari, Nour, Mahmood, Malaika, Mahmood, Mikail, Matin, Hossein Nick Zinat, Mcquade, Sean, Ramadan, Rabie, Urieli, Daniel, Wang, Xia, Wang, Yanbing, Xu, Rita, Yao, Mengsha, You, Yiling, Zachár, Gergely, Zhao, Yibo, Ameli, Mostafa, Baig, Mirza Najamuddin, Bhaskaran, Sarah, Butts, Kenneth, Gowda, Manasi, Janssen, Caroline, Lee, John, Pedersen, Liam, Wagner, Riley, Zhang, Zimo, Zhou, Chang, Work, Daniel B., Seibold, Benjamin, Sprinkle, Jonathan, Piccoli, Benedetto, Monache, Maria Laura Delle, Bayen, Alexandre M.
The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. These "phantom jams" or "stop-and-go waves,"are a significant source of wasted energy. Toward this goal, the CIRC
Externí odkaz:
http://arxiv.org/abs/2402.17043
Autor:
Harake, Edward S., Linzey, Joseph R., Jiang, Cheng, Joshi, Rushikesh S., Zaki, Mark M., Jones, Jaes C., Khalsa, Siri S., Lee, John H., Wilseck, Zachary, Joseph, Jacob R., Hollon, Todd C., Park, Paul
Objective. Achieving appropriate spinopelvic alignment has been shown to be associated with improved clinical symptoms. However, measurement of spinopelvic radiographic parameters is time-intensive and interobserver reliability is a concern. Automate
Externí odkaz:
http://arxiv.org/abs/2402.06185
Autor:
Lee, John D., Richter, Jakob, Pfaller, Martin R., Szafron, Jason M., Menon, Karthik, Zanoni, Andrea, Ma, Michael R., Feinstein, Jeffrey A., Kreutzer, Jacqueline, Marsden, Alison L., Schiavazzi, Daniele E.
The substantial computational cost of high-fidelity models in numerical hemodynamics has, so far, relegated their use mainly to offline treatment planning. New breakthroughs in data-driven architectures and optimization techniques for fast surrogate
Externí odkaz:
http://arxiv.org/abs/2312.00854
A Python interface is developed for the GPWR Simulator to automatically simulate cyber-spoofing of different steam generator parameters and plant operation. Specifically, steam generator water level, feedwater flowrate, steam flowrate, valve position
Externí odkaz:
http://arxiv.org/abs/2311.17936
Estimating the uncertainty of deep learning models in a reliable and efficient way has remained an open problem, where many different solutions have been proposed in the literature. Most common methods are based on Bayesian approximations, like Monte
Externí odkaz:
http://arxiv.org/abs/2310.19686
We consider asymptotically hyperbolic manifolds whose metrics have Sobolev-class regularity, and introduce several technical tools for studying PDEs on such manifolds. Our results employ two novel families of function spaces suitable for metrics pote
Externí odkaz:
http://arxiv.org/abs/2206.12854