25 citations · 168 across the 38 of their papers we have counts for
11 papers · 1 filter
Improving Gradient-guided Nested Sampling for Posterior Inference
Pablo Lemos, Nikolay Malkin, Will Handley +3
We present a performant, general-purpose gradient-guided nested sampling algorithm, , combining the state of the art in differentiable programming, Hamiltonian slice sa…
Learning an Effective Evolution Equation for Particle-Mesh Simulations Across Cosmologies
Nicolas Payot, Pablo Lemos, Laurence Perreault-Levasseur +3
Particle-mesh simulations trade small-scale accuracy for speed compared to traditional, computationally expensive N-body codes in cosmological simulations. In this work, we show ho…
Unraveling the Mysteries of Galaxy Clusters: Recurrent Inference Deconvolution of X-ray Spectra
Carter Rhea, Julie Hlavacek-Larrondo, Ralph Kraft +3
In the realm of X-ray spectral analysis, the true nature of spectra has remained elusive, as observed spectra have long been the outcome of convolution between instrumental respons…
Bayesian Imaging for Radio Interferometry with Score-Based Priors
Noe Dia, M. J. Yantovski-Barth, Alexandre Adam +5
The inverse imaging task in radio interferometry is a key limiting factor to retrieving Bayesian uncertainties in radio astronomy in a computationally effective manner. We use a sc…
Active learning meets fractal decision boundaries: a cautionary tale from the Sitnikov three-body problem
Nicolas Payot, Mario Pasquato, Alessandro Alberto Trani +2
Chaotic systems such as the gravitational N-body problem are ubiquitous in astronomy. Machine learning (ML) is increasingly deployed to predict the evolution of such systems, e.g.…
The search for the lost attractor
Mario Pasquato, Syphax Haddad, Pierfrancesco Di Cintio +8
N-body systems characterized by inverse square attractive forces may display a self similar collapse known as the gravo-thermal catastrophe. In star clusters, collapse is halted by…