相关论文: Analysis of Polarimetry Data with Angular Uncertai…
While X-ray Spectroscopy, Timing and Imaging have improved verymuch since 1962, when the first astronomical non-solar source was discovered, especially with the launch of Newton/X-ray Multi-Mirror Mission, Rossi/X-ray Timing Explorer and…
Estimating the uncertainty of a model's prediction on a test point is a crucial part of ensuring reliability and calibration under distribution shifts. A minimum description length approach to this problem uses the predictive normalized…
Target motion analysis with wideband passive sonar has received much attention. Maximum likelihood probabilistic data-association (ML-PDA) represents an asymptotically efficient estimator for deterministic target motion, and is especially…
Accurate sensor placement is critical for modeling spatio-temporal systems such as environmental and climate processes. Neural Processes (NPs), particularly Convolutional Conditional Neural Processes (ConvCNPs), provide scalable…
We propose a physics-informed machine learning method for uncertainty quantification in high-dimensional inverse problems. In this method, the states and parameters of partial differential equations (PDEs) are approximated with truncated…
Focal plane X-ray polarimetry is intended for relatively bright sources with a negligible impact of background. However this might not be always possible for IXPE (Imaging X-ray Polarimetry Explorer) when observing faint extended sources…
$\gamma$ rays are emitted by cosmic sources by non-thermal processes that yield either non-polarized photons, such as those from $\pi^0$ decay in hadronic interactions, or linearly polarized photons from synchrotron radiation and the…
A simple, self-calibrating, rotating-waveplate polarimeter is largely insensitive to light intensity fluctuations and is shown to be useful for determining the Stokes parameters of light. This study shows how to minimize the in situ…
We present a novel Explainable methodology for Condition Monitoring, relying on healthy data only. Since faults are rare events, we propose to focus on learning the probability distribution of healthy observations only, and detect Anomalies…
The association between a continuous and an ordinal variable is commonly modeled through the polyserial correlation model. However, this model, which is based on a partially-latent normality assumption, may be misspecified in practice, due…
The maximum softmax probability (MSP) represents a default approach when evaluating uncertainty quantification for language model generation with structured output. Although cheap, it is often miscalibrated. Methods that probe the model's…
Learning-based approaches to verifying unknown Markov decision processes (MDPs) often employ uncertain MDPs. These models use, for example, confidence intervals to capture transition uncertainty and allow synthesis of policies that are…
We present a new approach for correcting instrumental polarization by modeling the non-depolarizing effects of a complex series of optical elements to determine physically realizable Mueller matrices. Provided that the Mueller matrix of the…
Possibilistic and qualitative POMDPs (pi-POMDPs) are counterparts of POMDPs used to model situations where the agent's initial belief or observation probabilities are imprecise due to lack of past experiences or insufficient data…
Direction-dependent instrumental polarisation introduces wide-field polarimetric aberrations and limits the dynamic range of low-frequency interferometric images. We therefore provide a detailed two-dimensional analysis of the Giant…
Data driven modelling is vital to many analyses at collider experiments, however the derived inference of physical properties becomes subject to details of the model fitting procedure. This work brings a principled Bayesian picture, based…
The precision physics program of the ILC requires precise knowledge of the state of beam polarisation. In fact the Compton polarimeters intended for the ILC will have to measure the polarisation with error a factor of 2 smaller than the…
One of the critical challenges in automated driving is ensuring safety of automated vehicles despite the unknown behavior of the other vehicles. Although motion prediction modules are able to generate a probability distribution associated…
In this paper, we investigate the applicability of the astrometric method to the determination of the lens parameters for gravitational microlensing events toward both the LMC and the Galactic bulge. For this analysis, we investigate the…
In the paper the step-by-step principles for making local model of electron density are described. They are based on modulation principle - electron density dependence on time is a product of a number of temporal variations caused by solar…