Zobrazeno 1 - 10
of 3 351
pro vyhledávání: '"Hosking, P"'
Autor:
Khalifa, Muhammad, Tan, Yi-Chern, Ahmadian, Arash, Hosking, Tom, Lee, Honglak, Wang, Lu, Üstün, Ahmet, Sherborne, Tom, Gallé, Matthias
Model merging has shown great promise at combining expert models, but the benefit of merging is unclear when merging ``generalist'' models trained on many tasks. We explore merging in the context of large (~100B) models, by recycling checkpoints that
Externí odkaz:
http://arxiv.org/abs/2412.04144
We present a solvable scenario for 3D reconnection in a sheared magnetic field. We consider a localized external force that is applied slowly and then maintained, generating an Alfv\'{e}nic perturbation that spreads along the field lines. Separation
Externí odkaz:
http://arxiv.org/abs/2412.01736
Autor:
Burgess, Mark A., Hosking, Brendan, Reguant, Roc, Kaphle, Anubhav, O'Brien, Mitchell J., Sng, Letitia M. F., Jain, Yatish, Bauer, Denis C.
Machine-generated data is a valuable resource for training Artificial Intelligence algorithms, evaluating rare workflows, and sharing data under stricter data legislations. The challenge is to generate data that is accurate and private. Current stati
Externí odkaz:
http://arxiv.org/abs/2410.16705
Autor:
Wickramarachchi, Anuradha, Tonni, Shakila, Majumdar, Sonali, Karimi, Sarvnaz, Kõks, Sulev, Hosking, Brendan, Rambla, Jordi, Twine, Natalie A., Jain, Yatish, Bauer, Denis C.
Enabling clinicians and researchers to directly interact with global genomic data resources by removing technological barriers is vital for medical genomics. AskBeacon enables Large Language Models to be applied to securely shared cohorts via the GA4
Externí odkaz:
http://arxiv.org/abs/2410.16700
Autor:
Parthipan, Raghul, Anand, Mohit, Christensen, Hannah M., Hosking, J. Scott, Wischik, Damon J.
Machine learning (ML) has recently shown significant promise in modelling atmospheric systems, such as the weather. Many of these ML models are autoregressive, and error accumulation in their forecasts is a key problem. However, there is no clear def
Externí odkaz:
http://arxiv.org/abs/2405.14714
Autor:
Vaughan, Anna, Markou, Stratis, Tebbutt, Will, Requeima, James, Bruinsma, Wessel P., Andersson, Tom R., Herzog, Michael, Lane, Nicholas D., Chantry, Matthew, Hosking, J. Scott, Turner, Richard E.
Weather forecasting is critical for a range of human activities including transportation, agriculture, industry, as well as the safety of the general public. Machine learning models have the potential to transform the complex weather prediction pipel
Externí odkaz:
http://arxiv.org/abs/2404.00411
We propose a method for unsupervised abstractive opinion summarization, that combines the attributability and scalability of extractive approaches with the coherence and fluency of Large Language Models (LLMs). Our method, HIRO, learns an index struc
Externí odkaz:
http://arxiv.org/abs/2403.00435
Autor:
Rogers, Martin S J, Fox, Maria, Fleming, Andrew, van Zeeland, Louisa, Wilkinson, Jeremy, Hosking, J. Scott
Synthetic Aperture Radar (SAR) imagery is the primary data type used for sea ice mapping due to its spatio-temporal coverage and the ability to detect sea ice independent of cloud and lighting conditions. Automatic sea ice detection using SAR imagery
Externí odkaz:
http://arxiv.org/abs/2401.06009
Motivated by explosive releases of energy in fusion, space and astrophysical plasmas, we consider the nonlinear stability of stratified magnetohydrodynamic (MHD) equilibria against two-dimensional interchanges of straight magnetic-flux tubes. We demo
Externí odkaz:
http://arxiv.org/abs/2401.01336
Publikováno v:
Hydrology and Earth System Sciences, Vol 28, Pp 4903-4925 (2024)
The rivers of High-mountain Asia provide freshwater to around 1.9 billion people. However, precipitation, the main driver of river flow, is still poorly understood due to limited in situ measurements in this area. Existing tools to interpolate these
Externí odkaz:
https://doaj.org/article/388979216f594986b5f1316ac6f3a645
