Zobrazeno 1 - 10
of 53 886
pro vyhledávání: '"P. A. Neal"'
This paper introduces a novel deconvolution algorithm, shift-invariant multi-linearity (SIML), which significantly enhances the analysis of data from a comprehensive two-dimensional gas chromatograph coupled to a mass spectrometric detector (GC$\time
Externí odkaz:
http://arxiv.org/abs/2412.12114
While protoplanetary disks (PPDs) are generally thought to dissipate within several Myr, recent observations have revealed gas in debris disks. The origin of this gas remains uncertain, with one possibility being the unexpectedly long survival of PPD
Externí odkaz:
http://arxiv.org/abs/2411.17114
Autor:
Hasegawa, Yasuhiro, Nakatani, Riouhei, Rebollido, Isabel, MacGregor, Meredith, Davidsson, Björn J. R., Lis, Dariusz C., Turner, Neal, Willacy, Karen
Publikováno v:
A&A 692, A227 (2024)
Debris disks embrace the formation and evolution histories of planetary systems. Recent detections of gas in these disks have received considerable attention, as its origin ties up ongoing disk evolution and the present composition of planet-forming
Externí odkaz:
http://arxiv.org/abs/2411.09011
Autor:
Howard, Ward S., MacGregor, Meredith A., Feinstein, Adina D., Vega, Laura D., Cody, Ann Marie, Turner, Neal J., Scott, Valerie J., Burt, Jennifer A., Venuti, Laura
Ultraviolet flare emission can drive photochemistry in exoplanet atmospheres and even serve as the primary source of uncertainty in atmospheric retrievals. Additionally, flare energy budgets are not well-understood due to a paucity of simultaneous ob
Externí odkaz:
http://arxiv.org/abs/2411.08092
Autor:
Zhang, David Junhao, Paiss, Roni, Zada, Shiran, Karnad, Nikhil, Jacobs, David E., Pritch, Yael, Mosseri, Inbar, Shou, Mike Zheng, Wadhwa, Neal, Ruiz, Nataniel
Recently, breakthroughs in video modeling have allowed for controllable camera trajectories in generated videos. However, these methods cannot be directly applied to user-provided videos that are not generated by a video model. In this paper, we pres
Externí odkaz:
http://arxiv.org/abs/2411.05003
A popular method for Neural Architecture Search (NAS) is based on growing networks via small local changes to the network's architecture called network morphisms. These methods start with a small seed network and progressively grow the network by add
Externí odkaz:
http://arxiv.org/abs/2411.05855
Autor:
Lambeta, Mike, Wu, Tingfan, Sengul, Ali, Most, Victoria Rose, Black, Nolan, Sawyer, Kevin, Mercado, Romeo, Qi, Haozhi, Sohn, Alexander, Taylor, Byron, Tydingco, Norb, Kammerer, Gregg, Stroud, Dave, Khatha, Jake, Jenkins, Kurt, Most, Kyle, Stein, Neal, Chavira, Ricardo, Craven-Bartle, Thomas, Sanchez, Eric, Ding, Yitian, Malik, Jitendra, Calandra, Roberto
Touch is a crucial sensing modality that provides rich information about object properties and interactions with the physical environment. Humans and robots both benefit from using touch to perceive and interact with the surrounding environment (Joha
Externí odkaz:
http://arxiv.org/abs/2411.02479
Autor:
Li, Jialu, Li, Yuanzhen, Wadhwa, Neal, Pritch, Yael, Jacobs, David E., Rubinstein, Michael, Bansal, Mohit, Ruiz, Nataniel
We introduce the concept of a generative infinite game, a video game that transcends the traditional boundaries of finite, hard-coded systems by using generative models. Inspired by James P. Carse's distinction between finite and infinite games, we l
Externí odkaz:
http://arxiv.org/abs/2410.18975
Autor:
Vukadinovic, Milos, Tang, Xiu, Yuan, Neal, Cheng, Paul, Li, Debiao, Cheng, Susan, He, Bryan, Ouyang, David
Echocardiography is the most widely used cardiac imaging modality, capturing ultrasound video data to assess cardiac structure and function. Artificial intelligence (AI) in echocardiography has the potential to streamline manual tasks and improve rep
Externí odkaz:
http://arxiv.org/abs/2410.09704
Autor:
Lawton, Neal, Padmakumar, Aishwarya, Gaspers, Judith, FitzGerald, Jack, Kumar, Anoop, Steeg, Greg Ver, Galstyan, Aram
QLoRA reduces the memory-cost of fine-tuning a large language model (LLM) with LoRA by quantizing the base LLM. However, quantization introduces quantization errors that negatively impact model performance after fine-tuning. In this paper we introduc
Externí odkaz:
http://arxiv.org/abs/2410.14713