Related papers: A Gaussian process framework for modelling stellar…
Gaussian processes have become a popular tool for nonparametric regression because of their flexibility and uncertainty quantification. However, they often use stationary kernels, which limit the expressiveness of the model and may be…
One of the focus areas of modern scientific research is to reveal mysteries related to genes and their interactions. The dynamic interactions between genes can be encoded into a gene regulatory network (GRN), which can be used to gain…
The ever increasing level of precision achieved by present and future radial-velocity instruments is opening the way to discovering very low-mass, long-period planets (e.g. solar-system analogs). These systems will be detectable as…
Gaussian processes (GP) for machine learning have been studied systematically over the past two decades and they are by now widely used in a number of diverse applications. However, GP kernel design and the associated hyper-parameter…
High precision spectrographs might exhibit temporal variations of their reference velocity or nightly zero point (NZP). One way to monitor the NZP is to measure bright stars, which are assumed to have an intrinsic radial velocity variation…
Over the past decade, a number of algorithms for full-field elastic strain estimation from neutron and X-ray measurements have been published. Many of the recently published algorithms rely on modelling the unknown strain field as a…
Photospheric stellar activity might be an important source of noise and confusion in the radial-velocity measurements. RV planet search surveys as well as follow-up of photometric transit surveys require a deeper understanding and…
Time-varying inhomogeneities on stellar surfaces constitute one of the largest sources of radial velocity (RV) error for planet detection and characterization. We show that stellar variations, because they manifest on coherent, rotating…
Stellar magnetic activity produces time-varying distortions in the photospheric line profiles of solar-type stars. These lead to systematic errors in high-precision radial-velocity measurements, which limit efforts to discover and measure…
Modeling sequential data has become more and more important in practice. Some applications are autonomous driving, virtual sensors and weather forecasting. To model such systems, so called recurrent models are frequently used. In this paper…
We use the Iocco et al. (2015) compilation of 2,780 circular velocity measurements to analyze the Milky Way rotation curve. We find that the error bars for individual measurements are non-gaussian, and hence instead derive median statistics…
While much research effort has been dedicated to scaling up sparse Gaussian process (GP) models based on inducing variables for big data, little attention is afforded to the other less explored class of low-rank GP approximations that…
The Gaussian process (GP) regression model is a widely employed surrogate modeling technique for computer experiments, offering precise predictions and statistical inference for the computer simulators that generate experimental data.…
We introduce Latent Gaussian Process Regression which is a latent variable extension allowing modelling of non-stationary multi-modal processes using GPs. The approach is built on extending the input space of a regression problem with a…
We carry out a comparative analysis of the performance of three algorithms widely used to identify significant periodicities in radial-velocity (RV) datasets: the Generalised Lomb-Scargle Periodogram (GLS), its modified version based on…
The incomplete sampling of data in complex polarization measurements from radio telescopes negatively affects both the rotation measure (RM) transfer function and the Faraday depth spectra derived from these data. Such gaps in polarization…
We present a novel approach for analysing radial velocity data that combines two features: all the planets are searched at once and the algorithm is fast. This is achieved by utilizing compressed sensing techniques, which are modified to be…
We explore the detection limits of the phase modulation (PM) method of finding binary systems among multi-periodic pulsating stars. The method is an attractive way of finding non-transiting planets in the habitable zones of intermediate…
Small rocky planets seem to be very abundant around low-mass M-type stars. Their actual planetary population is however not yet precisely understood. Currently several surveys aim to expand the statistics with intensive detection campaigns,…
Tens of thousands of solar-like oscillating stars have been observed by space missions. Their photometric variability in the Fourier domain can be parameterized by a sum of two super-Lorentizian functions for granulation and a…