Related papers: DeepTTV: Deep Learning Prediction of Hidden Exopla…
It is relatively rare for gas giant planets to have resonant or near-resonant companions, but these systems are particularly useful for constraining planet formation and migration models. In this study, we examine Kepler-1624b, a sub-Saturn…
We consider a decision-making problem where the environment varies both in space and time. Such problems arise naturally when considering e.g., the navigation of an underwater robot amidst ocean currents or the navigation of an aerial…
Inferring planetary parameters from transit timing variations is challenging for small exoplanets because their transits may be so weak that determination of individual transit timing is difficult or impossible. We implement a useful…
Although deep networks have been widely adopted, one of their shortcomings has been their blackbox nature. One particularly difficult problem in machine learning is multivariate time series (MVTS) classification. MVTS data arise in many…
Multivariate time series (MTS) anomaly detection identifies abnormal patterns where each timestamp contains multiple variables. Existing MTS anomaly detection methods fall into three categories: reconstruction-based, prediction-based, and…
Transit Timing Variations (TTVs) can be induced by a range of physical phenomena, including planet-planet interactions, planet-moon interactions, and stellar activity. Recent work has shown that roughly half of moons would induce fast TTVs…
Precise destination prediction of taxi trajectories can benefit many intelligent location based services such as accurate ad for passengers. Traditional prediction approaches, which treat trajectories as one-dimensional sequences and…
In recent years, some traffic information prediction methods have been proposed to provide the precise information of travel time, vehicle speed, and traffic flow for highways. However, big errors may be obtained by these methods for urban…
Due to the non-stationary nature, the distribution of real-world multivariate time series (MTS) changes over time, which is known as distribution drift. Most existing MTS forecasting models greatly suffer from distribution drift and degrade…
The discovery of habitable exoplanets has long been a heated topic in astronomy. Traditional methods for exoplanet identification include the wobble method, direct imaging, gravitational microlensing, etc., which not only require a…
Variations in the timing of transiting exoplanets provide a powerful tool detecting additional planets in the system. Thus, the aim of this paper is to discuss the plausibility of transit timing variations on the Qatar-1 system by means of…
Sufficiently modeling the correlations among variables (aka channels) is crucial for achieving accurate multivariate time series forecasting (MTSF). In this paper, we propose a novel technique called Temporal Query (TQ) to more effectively…
Exoplanetary science heavily relies on transit depth ($D$) measurements. Yet, as instrumental precision increases, the uncertainty on $D$ appears to increasingly drift from expectations driven solely by photon-noise. Here we characterize…
Considering the importance of investigating the transit timing variations (TTVs) of transiting exoplanets, we present a follow-up study of HAT-P-12b. We include six new light curves observed between 2011 and 2015 from three different…
In this PhD dissertation, I discuss issues of the Radial Velocities (RV) and transit methods. These techniques allow us to derive the mass and radius of an exoplanet, necessary to model its bulk structure and to have insight on its…
The forecasting of Multivariate Time Series (MTS) has long been an important but challenging task. Due to the non-stationary problem across long-distance time steps, previous studies primarily adopt stationarization method to attenuate the…
Research into light curves from stars (temporal variation of brightness) has completely changed how exoplanets are discovered or characterised. This study including star light curves from the Kepler dataset as a way to discover exoplanets…
Exoplanet detection by direct imaging is a difficult task: the faint signals from the objects of interest are buried under a spatially structured nuisance component induced by the host star. The exoplanet signals can only be identified when…
Precise radial velocity measurements have led to the discovery of ~100 extrasolar planetary systems. We investigate the uncertainty in the orbital solutions that have been fit to these observations. Understanding these uncertainties will…
The interpretation of the origin of observed exoplanets is usually done only qualitatively due to uncertainties of key parameters in planet formation models. To allow a quantitative methodology which traces back in time to the planet birth…