Zobrazeno 1 - 10
of 3 588
pro vyhledávání: '"Rampini"'
Autor:
Medi, Tejaswini, Rampini, Arianna, Reddy, Pradyumna, Jayaraman, Pradeep Kumar, Keuper, Margret
Autoregressive (AR) models have achieved remarkable success in natural language and image generation, but their application to 3D shape modeling remains largely unexplored. Unlike diffusion models, AR models enable more efficient and controllable gen
Externí odkaz:
http://arxiv.org/abs/2411.19037
Autor:
Sanghi, Aditya, Khani, Aliasghar, Reddy, Pradyumna, Rampini, Arianna, Cheung, Derek, Malekshan, Kamal Rahimi, Madan, Kanika, Shayani, Hooman
Large-scale 3D generative models require substantial computational resources yet often fall short in capturing fine details and complex geometries at high resolutions. We attribute this limitation to the inefficiency of current representations, which
Externí odkaz:
http://arxiv.org/abs/2411.08017
Autor:
Gaisl, Thomas, Musli, Naser, Baumgartner, Patrick, Meier, Marc, Rampini, Silvana K, Blozik, Eva, Battegay, Edouard, Kohler, Malcolm, Saxena, Shekhar
Publikováno v:
JMIR Research Protocols, Vol 9, Iss 12, p e23973 (2020)
BackgroundThe health aspects, disease frequencies, and specific health interests of prisoners and refugees are poorly understood. Importantly, access to the health care system is limited for this vulnerable population. There has been no systematic in
Externí odkaz:
https://doaj.org/article/527fa0b3e7dc45839b4ae9928a9c3955
Autor:
Hui, Ka-Hei, Sanghi, Aditya, Rampini, Arianna, Malekshan, Kamal Rahimi, Liu, Zhengzhe, Shayani, Hooman, Fu, Chi-Wing
Significant progress has been made in training large generative models for natural language and images. Yet, the advancement of 3D generative models is hindered by their substantial resource demands for training, along with inefficient, non-compact,
Externí odkaz:
http://arxiv.org/abs/2401.11067
Autor:
Hutchins, Jack, Alam, Shamiul, Rampini, Dana S., Oripov, Bakhrom G., McCaughan, Adam N., Aziz, Ahmedullah
The relentless pursuit of miniaturization and performance enhancement in electronic devices has led to a fundamental challenge in the field of circuit design and simulation: how to accurately account for the inherent stochastic nature of certain devi
Externí odkaz:
http://arxiv.org/abs/2311.05820
Autor:
Sanghi, Aditya, Jayaraman, Pradeep Kumar, Rampini, Arianna, Lambourne, Joseph, Shayani, Hooman, Atherton, Evan, Taghanaki, Saeid Asgari
Significant progress has recently been made in creative applications of large pre-trained models for downstream tasks in 3D vision, such as text-to-shape generation. This motivates our investigation of how these pre-trained models can be used effecti
Externí odkaz:
http://arxiv.org/abs/2307.03869
Superconducting electronics are among the most promising alternatives to conventional CMOS technology thanks to the ultra-fast speed and ultra-high energy efficiency of the superconducting devices. Having a cryogenic control processor is also a cruci
Externí odkaz:
http://arxiv.org/abs/2306.10244
Autor:
Oripov, Bakhrom G., Rampini, Dana S., Allmaras, Jason, Shaw, Matthew D., Nam, Sae Woo, Korzh, Boris, McCaughan, Adam N.
For the last 50 years, superconducting detectors have offered exceptional sensitivity and speed for detecting faint electromagnetic signals in a wide range of applications. These detectors operate at very low temperatures and generate a minimum of ex
Externí odkaz:
http://arxiv.org/abs/2306.09473