Zobrazeno 1 - 10
of 37 040
pro vyhledávání: '"A. Rajagopal"'
Autor:
Rajagopal, Shreya K., Polk, Thad A.
Exposure therapy, a standard treatment for anxiety disorders, relies on fear extinction. However, extinction recall is often limited to the spatial and temporal context in which it is learned leading to fear relapse in novel contexts or after delays.
Externí odkaz:
http://arxiv.org/abs/2411.08140
Autor:
Peddiraju, Sharadind, Rajagopal, Srini
The challenge of creating domain-centric embeddings arises from the abundance of unstructured data and the scarcity of domain-specific structured data. Conventional embedding techniques often rely on either modality, limiting their applicability and
Externí odkaz:
http://arxiv.org/abs/2410.20325
Training data attribution (TDA) methods aim to attribute model outputs back to specific training examples, and the application of these methods to large language model (LLM) outputs could significantly advance model transparency and data curation. Ho
Externí odkaz:
http://arxiv.org/abs/2410.17413
We propose a GPU accelerated proximal message passing algorithm for solving contingency-constrained DC optimal power flow problems (OPF). We consider a highly general formulation of OPF that uses a sparse device-node model and supports a broad range
Externí odkaz:
http://arxiv.org/abs/2410.17203
Large scale grid expansion planning studies are essential to rapidly and efficiently decarbonizing the electricity sector. These studies help policy makers and grid participants understand which renewable generation, storage, and transmission assets
Externí odkaz:
http://arxiv.org/abs/2410.13055
Autor:
Wei, Ran, Lee, Joseph, Wakayama, Shohei, Tschantz, Alexander, Heins, Conor, Buckley, Christopher, Carenbauer, John, Thiruvengada, Hari, Albarracin, Mahault, de Prado, Miguel, Horling, Petter, Winzell, Peter, Rajagopal, Renjith
Predicting future trajectories of nearby objects, especially under occlusion, is a crucial task in autonomous driving and safe robot navigation. Prior works typically neglect to maintain uncertainty about occluded objects and only predict trajectorie
Externí odkaz:
http://arxiv.org/abs/2410.10653
Autor:
Placco, Vinicius M., Gupta, Arvind F., Almeida-Fernandes, Felipe, Logsdon, Sarah E., Rajagopal, Jayadev, Holmbeck, Erika M., Roederer, Ian U., Della Costa, John, Fernandez, Pipa, Golub, Eli, Higuera, Jesus, Patel, Yatrik, Ridgway, Susan, Schweiker, Heidi
In this work, we present high-resolution (R~100,000), high signal-to-noise (S/N~800) spectroscopic observations for the well-known, bright, extremely metal-poor, carbon-enhanced star BD+44 493. We determined chemical abundances and upper limits for 1
Externí odkaz:
http://arxiv.org/abs/2410.08943
Autor:
Zhang, Tao, Venkatesaraman, Rajagopal, De, Rajat K., Malin, Bradley A., Vorobeychik, Yevgeniy
An ability to share data, even in aggregated form, is critical to advancing both conventional and data science. However, insofar as such datasets are comprised of individuals, their membership in these datasets is often viewed as sensitive, with memb
Externí odkaz:
http://arxiv.org/abs/2410.07414
Autor:
Stefansson, Gudmundur, Mahadevan, Suvrath, Winn, Joshua, Marcussen, Marcus, Kanodia, Shubham, Albrecht, Simon, Fitzmaurice, Evan, Mikulskitye, One, Cañas, Caleb, Espinoza-Retamal, Juan Ignacio, Zwart, Yiri, Krolikowski, Daniel, Hotnisky, Andrew, Robertson, Paul, Alvarado-Montes, Jaime A., Bender, Chad, Blake, Cullen, Callingham, Joe, Cochran, William, Delamer, Megan, Diddams, Scott, Dong, Jiayin, Fernandes, Rachel, Giovanazzi, Mark, Halverson, Samuel, Libby-Roberts, Jessica, Logsdon, Sarah E, McElwain, Michael, Ninan, Joe, Rajagopal, Jayadev, Reji, Varghese, Roy, Arpita, Schwab, Christian, Wright, Jason
Gaia astrometry of nearby stars is precise enough to detect the tiny displacements induced by substellar companions, but radial velocity data are needed for definitive confirmation. Here we present radial velocity follow-up observations of 28 M and K
Externí odkaz:
http://arxiv.org/abs/2410.05654
Autor:
Elnoor, Mohamed, Weerakoon, Kasun, Seneviratne, Gershom, Xian, Ruiqi, Guan, Tianrui, Jaffar, Mohamed Khalid M, Rajagopal, Vignesh, Manocha, Dinesh
We present a novel autonomous robot navigation algorithm for outdoor environments that is capable of handling diverse terrain traversability conditions. Our approach, VLM-GroNav, uses vision-language models (VLMs) and integrates them with physical gr
Externí odkaz:
http://arxiv.org/abs/2409.20445