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Increasing model size when pretraining natural language representations often\nresults in improved performance on downstream tasks. However, at some point\nfurther model increas...
Federated learning involves training statistical models over remote devices or siloed data centers, such as mobile phones or hospitals, while keeping data localized. Training in...
In this study, we present conformational energies for a molecular mechanical model (Parm99) developed for organic and biological molecules using the restrained electrostatic pot...
Background The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. Objective To evaluate the risk of serious adverse outcomes in patients with COVID-19 b...
We present cosmological parameter results from the final full-mission Planck\nmeasurements of the CMB anisotropies. We find good consistency with the\nstandard spatially-flat 6-...
Abstract Objective To characterise the clinical features of patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United Kingdom during the growth phase ...
The adoption of a Reconfigurable Intelligent Surface (RIS) for downlink multi-user communication from a multi-antenna base station is investigated in this paper. We develop ener...
We study whether a depth two neural network can learn another depth two network using gradient descent. Assuming a linear output node, we show that the question of whether gradi...
17,187 patients entering 417 hospitals up to 24 hours (median 5 hours) after the onset of suspected acute myocardial infarction were randomised, with placebo control, between: (...
Most modern convolutional neural networks (CNNs) used for object recognition are built using the same principles: Alternating convolution and max-pooling layers followed by a sm...
[ Note by Dr. O. H. Wansbrough-Jones —Shortly before Professor Haber died, he gave the manuscript of this paper to Professor Sir William Pope. The final revision for the press h...