Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...
A new technique can help researchers who use Bayesian inference achieve more accurate results more quickly, without a lot of additional work. Pollsters trying to predict presidential election results ...
Uncertainty quantification (UQ) is increasingly critical for modelling complex systems in which input parameters or environmental conditions vary unpredictably. Polynomial chaos methods offer a ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
The newest journal from the Society for Industrial and Applied Mathematics, SIAM/ASA Journal on Uncertainty Quantification (JUQ), launched today with its first seven papers publishing online to Volume ...
(Nanowerk Spotlight) Standards, in a scientific context, have a much larger role in our society than just agreeing measurements. As the British Standards Institution (BSI) explains it, put at its ...
The rise of wearable technology has enabled unprecedented continuous data collection, opening new frontiers in health monitoring, activity recognition, and personalized medicine. This abundant sensor ...
PV yield forecasts are widely considered to be inaccurate, partly because they underestimate uncertainty. Image: Tilt Renewables. The uncertainty in energy yield forecasts is frequently underestimated ...
Validation of the probabilistic machine learning framework using the SpT model against the OCO-2 Level 2 data product. (A) Scatter density plots comparing XCO2 values and associated uncertainties from ...
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