相关论文: A Bayesian algorithm for model selection applied t…

In applications of Bayesian procedures, once a class of priors has been chosen, it may be tempting to fix the prior's hyperparameters from the data, in an empirical Bayes (EB) fashion, usually by their maximum marginal likelihood estimates…

In a line caustic crossing microlensing event, the caustic line moving across the surface of the source star provides a direct method to measure the integrated luminosity profile of the star. Combined with the enormous brightening at the…

The MACHO collaboration has recently analyzed 2.1 years of photometric data for about 8.5 million stars in the Large Magellanic Cloud (LMC). This analysis has revealed 8 candidate microlensing events and a total microlensing optical depth…

Extensive simulations of planetary microlensing are necessary both before and after a survey is conducted: before to design and optimize the survey and after to understand its detection efficiency. The major bottleneck in such computations…

The search for primordial gravitational waves in the Cosmic Microwave Background (CMB) will soon be limited by our ability to remove the lensing contamination to $B$-mode polarization. The often-used quadratic estimator for lensing is known…

We present the analysis of microlensing event MOA-2010-BLG-117, and show that the light curve can only be explained by the gravitational lensing of a binary source star system by a star with a Jupiter mass ratio planet. It was necessary to…

With a Bayesian approach, the linear optics correction algorithm for storage rings is revisited. Starting from the Bayes' theorem, a complete linear optics model is simplified as "likelihood functions" and "prior probability distributions".…

Bayesian model selection provides a powerful framework for objectively comparing models directly from observed data, without reference to ground truth data. However, Bayesian model selection requires the computation of the marginal…

Gaussian graphical models are used for determining conditional relationships between variables. This is accomplished by identifying off-diagonal elements in the inverse-covariance matrix that are non-zero. When the ratio of variables (p) to…

Microlensing light curves are now being monitored with the precision required to detect small perturbations due to planetary companions of the primary lens. Microlensing is complementary to other planetary search techniques in its potential…

We present the analyses of two short-timescale $(t_{\rm E} \sim 5~{\rm days})$ microlensing events, KMT-2016-BLG-1820 and KMT-2016-BLG-2142. In both light curves, the brief anomalies were clearly captured and densely covered by the Korea…

We present the observations of the binary lensing event MACHO-98-SMC-1 conducted at the Mt.~Stromlo 74" telescope by the Microlensing Planet Search (MPS) collaboration. The MPS data constrain the first caustic crossing to have occurred…

We report the result of the analysis of a dramatic repeating gravitational microlensing event OGLE-2009-BLG-092/MOA-2009-BLG-137, for which the light curve is characterized by two distinct peaks with perturbations near both peaks. We find…

We report a giant exoplanet discovery in the microlensing event OGLE-2017-BLG-1049, which is a planet-host star mass ratio of $q=9.53\pm0.39\times10^{-3}$ and has a caustic crossing feature in the Korea Microlensing Telescope Network…

Gravitational microlensing events are powerful tools for the study of stellar populations. In particular, they can be used to discover and study a variety of binary systems. A large number of binary lenses have already been found through…

We present a systematic search for parallax microlensing events among a total of 512 microlensing candidates in the OGLE II database for the 1997-1999 seasons. We fit each microlensing candidate with both the standard microlensing model and…

This study commenced by cross-matching data from the GAIA and OGLE telescopes with the aim of resolving the source star, long after microlensing is finished. The aim is breaking degeneracy between parameters of the microlensing equation,…

We present a hierarchical Bayesian learning approach to infer jointly sparse parameter vectors from multiple measurement vectors. Our model uses separate conditionally Gaussian priors for each parameter vector and common gamma-distributed…

It is proposed in the literature that in some complicated problems maximum likelihood estimates (MLE) are not suitable or even do not exist. An alternative to MLE for estimation of the parameters is the Bayesian method. The Markov chain…

Current causal discovery approaches require restrictive model assumptions in the absence of interventional data to ensure structure identifiability. These assumptions often do not hold in real-world applications leading to a loss of…