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Found 5 papers, 1 papers with code
Uncertainty quantification in automated valuation models with locally weighted conformal prediction
Non-parametric machine learning models, such as random forests and gradient boosted trees, are frequently used to estimate house prices due to their predictive accuracy, but such methods are often limited in their ability to quantify prediction uncertainty.
Valid Inference for Machine Learning Model Parameters
However, this can come with the risk of overtraining; in order for the model to generalize well, it is of great importance that we are able to find the optimal parameter for the model on the entire population -- not only on the given training sample.
Transfer Learning with Uncertainty Quantification: Random Effect Calibration of Source to Target (RECaST)
Most existing transfer learning approaches are based on fine-tuning pre-trained neural network models, and fail to provide crucial uncertainty quantification.
A Tale of Two Transition Disks: ALMA long-baseline observations of ISO-Oph 2 reveal two closely packed non-axisymmetric rings and a $\sim$2 au cavity
ISO-Oph 2 is a wide-separation (240 au) binary system where the primary star harbors a massive (M$_{dust}$ $\sim$40 M$_{\oplus}$) ring-like disk with a dust cavity $\sim$50 au in radius and the secondary hosts a much lighter (M$_{dust}$ $\sim$0. 8 M$_{\oplus}$) disk.
Earth and Planetary Astrophysics Solar and Stellar Astrophysics 85-11 J.2
The ALMA Early Science view of FUor/EXor objects. I. Through the looking-glass of V2775 Ori
We report the detection of a marginally resolved circumstellar disc in the ALMA continuum with an integrated flux of $106 \pm 2$ mJy, characteristic radius of $\sim$ 30 au, inclination of $14. 0^{+7. 8}_{-14. 5}$ deg, and is oriented nearly face-on with respect to the plane of the sky.
Solar and Stellar Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics
