Zobrazeno 1 - 10
of 4 482
pro vyhledávání: '"Aren A"'
Autor:
Brandon Hill, Ben Schafer, Nolan Vargas, Danny Zamora, Rohan Shrotri, Sarahi Perez, Geoffrey Farmer, Aren Avon, Anirudh Pai, Hirotada Mori, Jianmin Zhong
Publikováno v:
Ticks and Tick-Borne Diseases, Vol 14, Iss 6, Pp 102217- (2023)
Nutritive symbiosis between bacteria and ticks is observed across a range of ecological contexts; however, little characterization on the molecular components responsible for this symbiosis has been done. Previous studies in our lab demonstrated that
Externí odkaz:
https://doaj.org/article/af1104e07bad4f17a85b9d0319fbca83
To ensure their safe use, autonomous vehicles (AVs) must meet rigorous certification criteria that involve executing maneuvers safely within (arbitrary) scenarios where other actors perform their intended maneuvers. For that purpose, existing scenari
Externí odkaz:
http://arxiv.org/abs/2410.07079
Autor:
Chen, Yinpeng, Hutchins, DeLesley, Jansen, Aren, Zhmoginov, Andrey, Racz, David, Andersen, Jesper
We present MELODI, a novel memory architecture designed to efficiently process long documents using short context windows. The key principle behind MELODI is to represent short-term and long-term memory as a hierarchical compression scheme across bot
Externí odkaz:
http://arxiv.org/abs/2410.03156
Many practical applications of optimal control are subject to real-time computational constraints. When applying model predictive control (MPC) in these settings, respecting timing constraints is achieved by limiting the number of iterations of the o
Externí odkaz:
http://arxiv.org/abs/2409.11351
In this paper, we consider the problem of predicting unknown targets from data. We propose Online Residual Learning (ORL), a method that combines online adaptation with offline-trained predictions. At a lower level, we employ multiple offline predict
Externí odkaz:
http://arxiv.org/abs/2409.04069
Autor:
Dobson, Matthew M., Schwamb, Megan E., Fitzsimmons, Alan, Schambeau, Charles, Beck, Aren, Denneau, Larry, Erasmus, Nicolas, Heinze, A. N., Shingles, Luke J., Siverd, Robert J., Smith, Ken W., Tonry, John L., Weiland, Henry, Young, David. R., Kelley, Michael S. P., Lister, Tim, Bernardinelli, Pedro H., Ferrais, Marin, Jehin, Emmanuel, Fedorets, Grigori, Benecchi, Susan D., Verbiscer, Anne J., Murtagh, Joseph, Duffard, Rene, Gomez, Edward, Chatelain, Joey, Greenstreet, Sarah
Centaurs are small Solar System objects on chaotic orbits in the giant planet region, forming an evolutionary continuum with the Kuiper belt objects and Jupiter-family comets. Some Centaurs are known to exhibit cometary activity, though unlike comets
Externí odkaz:
http://arxiv.org/abs/2407.14410
Autor:
Kim, Gwanghyun, Martinez, Alonso, Su, Yu-Chuan, Jou, Brendan, Lezama, José, Gupta, Agrim, Yu, Lijun, Jiang, Lu, Jansen, Aren, Walker, Jacob, Somandepalli, Krishna
Training diffusion models for audiovisual sequences allows for a range of generation tasks by learning conditional distributions of various input-output combinations of the two modalities. Nevertheless, this strategy often requires training a separat
Externí odkaz:
http://arxiv.org/abs/2405.13762
Autor:
Tomar, Anshul S., Perzanowski, Shaede, Mejia-Alvarez, Ricardo, Mukherjee, Ranjan, Hellum, Aren M., Kamensky, Kristina M.
The wall shear stress generated by a Bernoulli pad over a workpiece is of interest for the particular application of non-contact biofouling mitigation from ship hulls. The shear stress distribution has been determined numerically in the literature; i
Externí odkaz:
http://arxiv.org/abs/2404.15463
Autor:
Wei, Ting-Ruen, Hell, Michele, Le, Dang Bich Thuy, Vierra, Aren, Pang, Ran, Patel, Mahesh, Kang, Young, Yan, Yuling
This study presents an unsupervised domain adaptation method aimed at autonomously generating image masks outlining regions of interest (ROIs) for differentiating breast lesions in breast ultrasound (US) imaging. Our semi-supervised learning approach
Externí odkaz:
http://arxiv.org/abs/2404.12450
Continuous-time adaptive controllers for systems with a matched uncertainty often comprise an online parameter estimator and a corresponding parameterized controller to cancel the uncertainty. However, such methods are often impossible to implement d
Externí odkaz:
http://arxiv.org/abs/2404.02023