Zobrazeno 1 - 10
of 24 450
pro vyhledávání: '"P Parikh"'
For most health or well-being interventions, the process of evaluation is distinct from the activity itself, both in terms of who is involved, and how the actual data is collected and analyzed. Tangible interaction affords the opportunity to combine
Externí odkaz:
http://arxiv.org/abs/2410.24036
Autor:
Wijk, Hjalmar, Lin, Tao, Becker, Joel, Jawhar, Sami, Parikh, Neev, Broadley, Thomas, Chan, Lawrence, Chen, Michael, Clymer, Josh, Dhyani, Jai, Ericheva, Elena, Garcia, Katharyn, Goodrich, Brian, Jurkovic, Nikola, Kinniment, Megan, Lajko, Aron, Nix, Seraphina, Sato, Lucas, Saunders, William, Taran, Maksym, West, Ben, Barnes, Elizabeth
Frontier AI safety policies highlight automation of AI research and development (R&D) by AI agents as an important capability to anticipate. However, there exist few evaluations for AI R&D capabilities, and none that are highly realistic and have a d
Externí odkaz:
http://arxiv.org/abs/2411.15114
Autor:
Liu, Xin-Yang, Parikh, Meet Hemant, Fan, Xiantao, Du, Pan, Wang, Qing, Chen, Yi-Fan, Wang, Jian-Xun
Eddy-resolving turbulence simulations require stochastic inflow conditions that accurately replicate the complex, multi-scale structures of turbulence. Traditional recycling-based methods rely on computationally expensive precursor simulations, while
Externí odkaz:
http://arxiv.org/abs/2411.14378
Sequential learning in a multi-agent resource constrained matching market has received significant interest in the past few years. We study decentralized learning in two-sided matching markets where the demand side (aka players or agents) competes fo
Externí odkaz:
http://arxiv.org/abs/2411.11794
Publikováno v:
International Symposium on Academic Makerspaces. 6 (2021)
CRAFT@Large (C@L) is an initiative launched by the MakerLAB at Cornell Tech to create an inclusive environment for the intercultural and intergenerational exchange of ideas through making. With our approach, we challenge the traditional definition of
Externí odkaz:
http://arxiv.org/abs/2410.23239
Autor:
Schneider, Helen, Nowak, Sebastian, Parikh, Aditya, Layer, Yannik C., Theis, Maike, Block, Wolfgang, Sprinkart, Alois M., Attenberger, Ulrike, Sifa, Rafet
Image-based diagnostic decision support systems (DDSS) utilizing deep learning have the potential to optimize clinical workflows. However, developing DDSS requires extensive datasets with expert annotations and is therefore costly. Leveraging report
Externí odkaz:
http://arxiv.org/abs/2410.21014
Long-range attractive interactions between dark matter particles can significantly enhance their annihilation, particularly at low velocities. This ``Sommerfeld enhancement'' is typically computed by evaluating the deformation of the two-particle wav
Externí odkaz:
http://arxiv.org/abs/2410.18168
Autor:
Parikh, Krish
Smart vehicles produce large amounts of data, much of which is sensitive and at risk of privacy breaches. As attackers increasingly exploit anonymised metadata within these datasets to profile drivers, it's important to find solutions that mitigate t
Externí odkaz:
http://arxiv.org/abs/2410.08462
This paper presents a computationally efficient model predictive control formulation that uses an integral Chebyshev collocation method to enable rapid operations of autonomous agents. By posing the finite-horizon optimal control problem and recursiv
Externí odkaz:
http://arxiv.org/abs/2410.07413
The sensitivity of electron EDM experiments has been increasing at a rapid pace, and could yield indications of new physics in the coming decade. An intriguing possibility is that an EDM signal could be generated by new, electroweak-charged particles
Externí odkaz:
http://arxiv.org/abs/2410.01873