Count data modelling comprises a suite of statistical techniques dedicated to analysing non-negative integer-valued observations. Such data often arise in a variety of contexts including epidemiology, ...
Artificial intelligence (AI) is increasingly used to analyze medical images, materials data and scientific measurements, but ...
Uncertainty quantification (UQ) is a field of study that focuses on understanding, modeling, and reducing uncertainties in computational models and real-world systems. It is widely used in engineering ...
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Model steering is a more efficient way to train AI models
Training artificial intelligence models is costly. Researchers estimate that training costs for the largest frontier models ...
The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...
Theoretical and simulation estimates of turbulent transport (high-dimensional data that depend on plasma conditions such as density, temperature, and magnetic field) are used as low-fidelity data, and ...
The built environment faces increasing pressures from climate change, resource limitations, and rapid urbanisation.
A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.
Count data modelling occupies a central role in statistical applications across diverse disciplines including epidemiology, econometrics and engineering. Traditionally, the Poisson distribution has ...
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