Zobrazeno 1 - 10
of 45 953
pro vyhledávání: '"Snell"'
Autor:
Conway RB, Gerard Gonzalez A, Shah VN, Geno Rasmussen C, Akturk HK, Pyle L, Forlenza G, Alonso GT, Snell-Bergeon J
Publikováno v:
Diabetes, Metabolic Syndrome and Obesity, Vol Volume 16, Pp 2295-2310 (2023)
Rebecca Baqiyyah Conway,1 Andrea Gerard Gonzalez,2 Viral N Shah,2 Cristy Geno Rasmussen,2 Halis Kaan Akturk,2 Laura Pyle,2 Gregory Forlenza,2 Guy Todd Alonso,2 Janet Snell-Bergeon2 1Department of Epidemiology, Colorado School of Public Health, Univer
Externí odkaz:
https://doaj.org/article/bcbdf8c348d14433a259038f880da983
Genome Finland tells a story of genomic medicine in Finland from the study of rare Finnish diseases in the 1960s and 1970s to the implementation of personalized medicine in the 2020s. The main focus is on the 21st century – the period after the Hum
Externí odkaz:
https://library.oapen.org/handle/20.500.12657/91187
Publikováno v:
Infection and Drug Resistance, Vol Volume 14, Pp 5293-5301 (2021)
Jaideep Vazirani,1 Thomas Crowhurst,1,2 C Orla Morrissey,3 Gregory I Snell1 1Lung Transplant Service, Department of Respiratory Medicine, The Alfred Hospital and Monash University, Melbourne, VIC, Australia; 2Department of Medicine, The University of
Externí odkaz:
https://doaj.org/article/d7bfe93badb844a3a207c973095ac32a
Enabling LLMs to improve their outputs by using more test-time computation is a critical step towards building generally self-improving agents that can operate on open-ended natural language. In this paper, we study the scaling of inference-time comp
Externí odkaz:
http://arxiv.org/abs/2408.03314
Autor:
Riley, Richard D, Collins, Gary S, Whittle, Rebecca, Archer, Lucinda, Snell, Kym IE, Dhiman, Paula, Kirton, Laura, Legha, Amardeep, Liu, Xiaoxuan, Denniston, Alastair, Harrell Jr, Frank E, Wynants, Laure, Martin, Glen P, Ensor, Joie
When developing a clinical prediction model, the sample size of the development dataset is a key consideration. Small sample sizes lead to greater concerns of overfitting, instability, poor performance and lack of fairness. Previous research has outl
Externí odkaz:
http://arxiv.org/abs/2407.09293
Autor:
Atkins, Carolyn, Chahid, Younes, Lister, Gregory, Tuck, Rhys, Kotlewski, Richard, Snell, Robert M., Livera, Elaine R., Faour, Mariam, Todd, Iain, Deffley, Robert, Shipley, James, Walsh, Tom, Gardstam, Johannes, Bourgenot, Cyril, White, Paul, Davies, Spencer, Tammas-Williams, Samuel
Additive manufacturing (AM; 3D printing) in aluminium using laser powder bed fusion provides a new design space for lightweight mirror production. Printing layer-by-layer enables the use of intricate lattices for mass reduction, as well as organic sh
Externí odkaz:
http://arxiv.org/abs/2407.07405
Autor:
Whittle, Rebecca, Ensor, Joie, Archer, Lucinda, Collins, Gary S., Dhiman, Paula, Denniston, Alastair, Alderman, Joseph, Legha, Amardeep, van Smeden, Maarten, Moons, Karel G., Cazier, Jean-Baptiste, Riley, Richard D., Snell, Kym I. E.
When evaluating the performance of a model for individualised risk prediction, the sample size needs to be large enough to precisely estimate the performance measures of interest. Current sample size guidance is based on precisely estimating calibrat
Externí odkaz:
http://arxiv.org/abs/2406.19673
Autor:
Marjieh, Raja, Kumar, Sreejan, Campbell, Declan, Zhang, Liyi, Bencomo, Gianluca, Snell, Jake, Griffiths, Thomas L.
Humans rely on strong inductive biases to learn from few examples and abstract useful information from sensory data. Instilling such biases in machine learning models has been shown to improve their performance on various benchmarks including few-sho
Externí odkaz:
http://arxiv.org/abs/2405.19420
Over the past several years, the misidentification of SpaceX Starlink satellites as Unidentified Aerial Phenomena (UAP) by pilots and laypersons has generated unnecessary aviation risk and confusion. The many deployment and orbital evolution strategi
Externí odkaz:
http://arxiv.org/abs/2403.08155
Autor:
Amirizaniani, Maryam, Yao, Jihan, Lavergne, Adrian, Okada, Elizabeth Snell, Chadha, Aman, Roosta, Tanya, Shah, Chirag
As Large Language Models (LLMs) become more pervasive across various users and scenarios, identifying potential issues when using these models becomes essential. Examples of such issues include: bias, inconsistencies, and hallucination. Although audi
Externí odkaz:
http://arxiv.org/abs/2402.09346