Zobrazeno 1 - 10
of 4 889
pro vyhledávání: '"Busby, P. A."'
Graph neural networks (GNN) have shown significant capabilities in handling structured data, yet their application to dynamic, temporal data remains limited. This paper presents a new type of graph attention network, called TempoKGAT, which combines
Externí odkaz:
http://arxiv.org/abs/2408.16391
Accurately forecasting dynamic processes on graphs, such as traffic flow or disease spread, remains a challenge. While Graph Neural Networks (GNNs) excel at modeling and forecasting spatio-temporal data, they often lack the ability to directly incorp
Externí odkaz:
http://arxiv.org/abs/2408.16379
Autor:
Busby, Ian, Lazzati, Davide
We analyze the spectral evolution of 62 bright Fermi gamma-ray bursts with large enough signal to noise to allow for time resolved spectral analysis. We develop a new algorithm to test for single-pulse morphology that is insensitive to the specific s
Externí odkaz:
http://arxiv.org/abs/2407.12926
Physics-informed neural networks (PINNs) have gained significant prominence as a powerful tool in the field of scientific computing and simulations. Their ability to seamlessly integrate physical principles into deep learning architectures has revolu
Externí odkaz:
http://arxiv.org/abs/2404.03240
Generative Artificial Intelligence (GAI) represents an emerging field that promises the creation of synthetic data and outputs in different modalities. GAI has recently shown impressive results across a large spectrum of applications ranging from bio
Externí odkaz:
http://arxiv.org/abs/2402.03349
Autor:
Nathan Dwarshuis, Divya Kalra, Jennifer McDaniel, Philippe Sanio, Pilar Alvarez Jerez, Bharati Jadhav, Wenyu (Eddy) Huang, Rajarshi Mondal, Ben Busby, Nathan D. Olson, Fritz J. Sedlazeck, Justin Wagner, Sina Majidian, Justin M. Zook
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Despite the growing variety of sequencing and variant-calling tools, no workflow performs equally well across the entire human genome. Understanding context-dependent performance is critical for enabling researchers, clinicians, and develope
Externí odkaz:
https://doaj.org/article/cea87d7d5cfe495988b6700aa70955a2
Autor:
Kaufmann, Basil, Busby, Dallin, Das, Chandan Krushna, Tillu, Neeraja, Menon, Mani, Tewari, Ashutosh K., Gorin, Michael A.
Objectives: To describe the development and validation of a zero-shot learning natural language processing (NLP) tool for abstracting data from unstructured text contained within PDF documents, such as those found within electronic health records. Ma
Externí odkaz:
http://arxiv.org/abs/2308.00107
Autor:
Rytting, Christopher Michael, Sorensen, Taylor, Argyle, Lisa, Busby, Ethan, Fulda, Nancy, Gubler, Joshua, Wingate, David
Researchers often rely on humans to code (label, annotate, etc.) large sets of texts. This kind of human coding forms an important part of social science research, yet the coding process is both resource intensive and highly variable from application
Externí odkaz:
http://arxiv.org/abs/2306.02177
Autor:
Natalie Busby, Sarah Newman-Norlund, Sara Sayers, Chris Rorden, Roger Newman-Norlund, Janina Wilmskoetter, Rebecca Roth, Sarah Wilson, Deena Schwen-Blackett, Sigfus Kristinsson, Alex Teghipco, Julius Fridriksson, Leonardo Bonilha
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-12 (2024)
Abstract Premature brain aging is associated with poorer cognitive reserve and lower resilience to injury. When there are focal brain lesions, brain regions may age at different rates within the same individual. Therefore, we hypothesize that reduced
Externí odkaz:
https://doaj.org/article/8566612a90b4461496ff8b8bb48e070c
Autor:
Argyle, Lisa P., Busby, Ethan, Gubler, Joshua, Bail, Chris, Howe, Thomas, Rytting, Christopher, Wingate, David
A rapidly increasing amount of human conversation occurs online. But divisiveness and conflict can fester in text-based interactions on social media platforms, in messaging apps, and on other digital forums. Such toxicity increases polarization and,
Externí odkaz:
http://arxiv.org/abs/2302.07268