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Incorporating constraints is a major concern in probabilistic machine learning. A wide variety of problems require predictions to be integrated with reasoning about constraints, from modelling routes on maps to approving loan predictions.…
Numerical analysis has no satisfactory method for the more realistic optimization models. However, with constraint programming one can compute a cover for the solution set to arbitrarily close approximation. Because the use of constraint…
The COMPAS public rapid binary population synthesis code has undergone a number of key improvements since the original COMPAS methods paper (Team COMPAS: Riley et al., 2022) was published. These include more sophisticated and robust…
Stellar population synthesis (SPS) models are a key tool for deriving the age, metallicity, radial velocity and reddening of star clusters from their integrated spectra. Using a sample of 129 star clusters with high-quality spectra, we…
Gaussian process regression is a popular Bayesian framework for surrogate modeling of expensive data sources. As part of a broader effort in scientific machine learning, many recent works have incorporated physical constraints or other a…
Boundary constraints in physical, environmental and engineering models restrict smooth states such as temperature to follow known physical laws at the edges of their spatio-temporal domain. Examples include fixed-state or fixed-derivative…
In order to increase the efficiency of the computer simulation of biological molecules, it is very common to impose holonomic constraints on the fastest degrees of freedom; normally bond lengths, but also possibly bond angles. However, as…
Using the StarTrack binary population synthesis code we model the population of double neutron stars in the Galaxy. We include a detailed treatment of the spin evolution of each pulsar due to processes such as spin-down and spin-up during…
In recent years the role of epidemic models in informing public health policies has progressively grown. Models have become increasingly realistic and more complex, requiring the use of multiple data sources to estimate all quantities of…
Synthetic population is an increasingly important material used in numerous areas such as urban and transportation analysis. Traditional methods such as iterative proportional fitting (IPF) is not capable of generating high-quality data…
Theoretical ecologists have long sought to understand how the persistence of populations depends on biotic and abiotic factors. Classical work showed that demographic stochasticity causes the mean time to extinction to increase…
Combining population synthesis models with simple Montecarlo simulations of stochastic effects in the number of stars occupying sparsely populated stellar evolutionary phases in the HRD, I show that the scatter observed in the photometric…
Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets…
The status of precision electroweak data, tests of the standard model, determination of its parameters, and constraints on new physics, are surveyed.
One way to extract more information from the integrated light of galaxies is to improve the spectral resolution at which observations and analysis are carried out. The population synthesis code currently providing the highest spectral…
In this work we introduce declarative statistics, a suite of declarative modelling tools for statistical analysis. Statistical constraints represent the key building block of declarative statistics. First, we introduce a range of relevant…
We compare six popularly used evolutionary population synthesis (EPS) models (BC03, CB07, Ma05, GALEV, GRASIL, Vazdekis/Miles) through fitting the full optical spectra of six representative types of galaxies (star-forming and composite…
We summarize here the discussions around photospheric constraints, current uncertainties in models of stellar atmospheres, and reports on ongoing spectroscopic surveys. Rather than a panorama of the state of the art, we chose to present a…
We test how well available stellar population models can reproduce observed u,g,r,i,z-band photometry of the local galaxy population (0.02<=z<=0.03) as probed by the SDSS. Our study is conducted from the perspective of a user of the models,…
While Shannon's mutual information has widespread applications in many disciplines, for practical applications it is often difficult to calculate its value accurately for high-dimensional variables because of the curse of dimensionality.…