相关论文: Toward Extremely Precise Radial Velocities: II. A …
Gaussian Process (GP) models provide a flexible framework for prediction and uncertainty quantification. For most covariance functions, however, exact GP prediction with $n$ points scales as $\mathcal{O}(n^3)$, making it prohibitively…
Pulsars are known to display short-term variability. Recently, examples of longer-term emission variability have emerged that are often correlated with changes in the rotational properties of the pulsar. To further illuminate this…
Stellar activity interferes with precise radial velocity measurements and limits our ability to detect and characterize planets, particularly Earth-like planets. We introduce \aestra (Auto-Encoding STellar Radial-velocity and Activity), a…
We introduce graph gamma process (GGP) linear dynamical systems to model real-valued multivariate time series. For temporal pattern discovery, the latent representation under the model is used to decompose the time series into a…
Dynamic simulators are computational models governed by differential equations that evolve over time. They are essential for scientific and engineering applications but remain challenging to emulate because of the unpredictable behavior of…
Gaussian processes are an important regression tool with excellent analytic properties which allow for direct integration of derivative observations. However, vanilla GP methods scale cubically in the amount of observations. In this work,…
We present a novel and efficient method for fitting dynamical models of stellar kinematic data in dwarf spheroidal galaxies (dSph). Our approach is based on Gaussian-process emulation (GPE), which is a sophisticated form of curve fitting…
Aims. With the purpose of determining the orbital parameters of exoplanetary systems from observational data, we have developed a software, named TRADES (TRAnsits and Dynamics of Exoplanetary Systems), to simultaneously fit observed radial…
Gaussian process (GP) emulators have become essential tools for approximating complex simulators, significantly reducing computational demands in optimization, sensitivity analysis, and model calibration. While traditional GP emulators…
Radar-based human activity recognition (HAR) still lacks a comprehensive simulation method. Existing software is developed based on models or motion-captured data, resulting in limited flexibility. To address this issue, a simulator that…
Gaussian processes are popular and flexible models for spatial, temporal, and functional data, but they are computationally infeasible for large datasets. We discuss Gaussian-process approximations that use basis functions at multiple…
The recent accelerated growth in the computing power has generated popularization of experimentation with dynamic computer models in various physical and engineering applications. Despite the extensive statistical research in computer…
In the gravitational-wave analysis of pulsar-timing-array datasets, parameter estimation is usually performed using Markov Chain Monte Carlo methods to explore posterior probability densities. We introduce an alternative procedure that…
It is difficult to discover pulsars via their gamma-ray emission because current instruments typically detect fewer than one photon per million rotations. This creates a significant computing challenge for isolated pulsars, where the…
Planetary studies demand precise and accurate stellar parameters as input to infer the planetary properties. Different methods often provide different results that could lead to biases in the planetary parameters. In this work, we present a…
Stellar signals are the main limitation for precise radial-velocity (RV) measurements. These signals arise from the photosphere of the stars. The m/s perturbation created by these signals prevents the detection and mass characterization of…
Empirical exoplanet mass-radius relations have been used to study the demographics and compositions of small exoplanets for many years. However, the heterogeneous nature of these measurements hinders robust statistical analysis of this…
The Kepler mission has provided high-accurate photometric data in a long time span for more than two hundred thousands stars, looking for planetary transits. Among the detected candidates, the planetary nature of around 15% has been…
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…
Gaussian Processes (GPs) are expressive models for capturing signal statistics and expressing prediction uncertainty. As a result, the robotics community has gathered interest in leveraging these methods for inference, planning, and…