Related papers: Understanding selection effects in observed sample…
Cataclysmic variables (CVs) exhibit a plethora of variable phenomena many of which require long, uninterrupted light curves to reveal themselves in detail. The month long datasets provided by TESS are well suited for this purpose. TESS has…
Accurate determinations of masses and radii in binary stars, along with estimates of the effective temperatures, metallicities, and other properties, have long been used to test models of stellar evolution. As might be expected,…
Machine learning systems increasingly depend on pipelines of multiple algorithms to provide high quality and well structured predictions. This paper argues interaction effects between clustering and prediction (e.g. classification,…
Upcoming weak lensing surveys will survey large cosmological volumes to measure the growth of cosmological structure with time and thereby constrain dark energy. One major systematic uncertainty in this process is the calibration of the…
Modern regression applications can involve hundreds or thousands of variables which motivates the use of variable selection methods. Bayesian variable selection defines a posterior distribution on the possible subsets of the variables…
While Neutral Theory famously describes the number of discrete genetic differences in populations, we consider the number of genetic backgrounds under which such differences are observed - setting limits to the generalizability of their…
Confirmation bias is a cognitive bias that adversely affects management decisions, and mathematical modelling is an aid to its detailed understanding. Bias in opinion update about the value of a parameter is modelled here assuming that…
Causal models are notoriously difficult to validate because they make untestable assumptions regarding confounding. New scientific experiments offer the possibility of evaluating causal models using prediction performance. Prediction…
We present the first population synthesis of synchronous magnetic cataclysmic variables, called polars, taking into account the effect of the white dwarf (WD) magnetic field on angular momentum loss. We implemented the reduced magnetic…
The discovery of extremely luminous galaxies at ultra-high redshifts ($z\gtrsim 8$) has challenged galaxy formation models. Most analyses of this tension have not accounted for the variance due to field-to-field clustering, which causes the…
Despite the major advances taken in causal modeling, causality is still an unfamiliar topic for many statisticians. In this paper, it is demonstrated from the beginning to the end how causal effects can be estimated from observational data…
We briefly review some constraints (Owing to the limited number of pages of present review, only a sub-sample of the topics discussed during the talk are briefly summarized. For the interested readers we are pleased to send them upon…
This is the second paper of a series which aims at quantifying the uncertainties in chemical evolution model predictions related to the underlying model assumptions. Specifically, it deals with the uncertainties due to the choice of the…
In the field of road safety, it is common to use responsibility analyses to assess the effect of a given factor on the risk of being responsible for an accident, among drivers involved in an accident only. Even if this design is now widely…
Causal inference is to estimate the causal effect in a causal relationship when intervention is applied. Precisely, in a causal model with binary interventions, i.e., control and treatment, the causal effect is simply the difference between…
In natural phenomena, data distributions often deviate from normality. One can think of cataclysms as a self-explanatory example: events that occur almost never, and at the same time are many standard deviations away from the common…
Binary interactions are commonplace among massive stars, giving rise observed phenomena such as X-ray binaries, stripped stars & supernovae, and gravitational-wave sources. The multiplicity properties of massive stars thus represent a…
Several observational works have attempted to isolate the effects of galaxy interactions by comparing galaxies in pairs with isolated galaxies. However, different authors have proposed different ways to build these so-called control samples…
In classical extreme value theory probabilities of extreme events are estimated assuming all the components of a random vector to be in a domain of attraction of an extreme value distribution. In contrast, the conditional extreme value…
We formulate a causal extension to the recently introduced paradigm of instance-wise feature selection to explain black-box visual classifiers. Our method selects a subset of input features that has the greatest causal effect on the models…