25 citations · 56 across the 5 of their papers we have counts for
7 papers
Accounting for stellar activity signals in radial-velocity data by using Change Point Detection techniques
U. Simola, A. Bonfanti, X. Dumusque +3
Active regions on the photosphere of a star have been the major obstacle for detecting Earth-like exoplanets using the radial velocity (RV) method. A commonly employed solution for…
ABC of the Future
Henri Pesonen, Umberto Simola, Alvaro Köhn-Luque +8
Approximate Bayesian computation (ABC) has advanced in two decades from a seminal idea to a practically applicable inference tool for simulator-based statistical models, which are…
Sequentially guided MCMC proposals for synthetic likelihoods and correlated synthetic likelihoods
Umberto Picchini, Umberto Simola, Jukka Corander
Synthetic likelihood (SL) is a strategy for parameter inference when the likelihood function is analytically or computationally intractable. In SL, the likelihood function of the d…
Adaptive Approximate Bayesian Computation Tolerance Selection
Umberto Simola, Jessica Cisewski-Kehe, Michael U. Gutmann +1
Approximate Bayesian Computation (ABC) methods are increasingly used for inference in situations in which the likelihood function is either computationally costly or intractable to…
Measuring precise radial velocities and cross-correlation function line-profile variations using a Skew Normal density
Umberto Simola, Xavier Dumusque, Jessi Cisewski-Kehe
Stellar activity is one of the primary limitations to the detection of low-mass exoplanets using the radial-velocity (RV) technique. We propose to estimate the variations in shape…
Machine Learning Accelerated Likelihood-Free Event Reconstruction in Dark Matter Direct Detection
U. Simola, B. Pelssers, D. Barge +2
Reconstructing the position of an interaction for any dual-phase time projection chamber (TPC) with the best precision is key to directly detecting Dark Matter. Using the likelihoo…