activity
20242026
most citedTackling the Problem of Distributional Shifts: Correcting Misspecified, High-Dimensional Data-Driven Priors for Inverse Problems

4 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

astro-ph.EP2026

POSTELLAR: Posterior Stellar Spectrum Sampling - An Alternative to Approximate Stellar Spectra for Exoplanetary Analysis

Dhvani Doshi, Nicolas B. Cowan, Yashar Hezaveh +2

We present a novel approach to perform posterior sampling of the underlying stellar spectrum in high-resolution spectroscopic observations. Our method, postellar, coherently combin…

stat.ML2026

MIRA: A Score for Conditional Distribution Accuracy and Model Comparison

Sammy Sharief, Justine Zeghal, Gabriel Missael Barco +3

We introduce Mira, a sample-based score for assessing the accuracy of a candidate conditional distribution using only joint samples from the true data-generating process. Relying o…

astro-ph.GA2025

Mind the Information Gap: Unveiling Detailed Morphologies of z 0.5-1.0 Galaxies with SLACS Strong Lenses and Data-Driven Analysis

Ronan Legin, Connor Stone, Alexandre Adam +5

We present new state-of-the-art lens models for strong gravitational lensing systems from the Sloan Lens ACS (SLACS) survey, developed within a Bayesian framework that employs high…

astro-ph.IM2025

Pixellated Posterior Sampling of Point Spread Functions in Astronomical Images

Connor Stone, Ronan Legin, Alexandre Adam +4

We introduce a novel framework for upsampled Point Spread Function (PSF) modeling using pixel-level Bayesian inference. Accurate PSF characterization is critical for precision meas…

astro-ph.IM2025

Blind Strong Gravitational Lensing Inversion: Joint Inference of Source and Lens Mass with Score-Based Models

Gabriel Missael Barco, Ronan Legin, Connor Stone +2

Score-based models can serve as expressive, data-driven priors for scientific inverse problems. In strong gravitational lensing, they enable posterior inference of a background gal…

astro-ph.IM2024★ 4 cited

Tackling the Problem of Distributional Shifts: Correcting Misspecified, High-Dimensional Data-Driven Priors for Inverse Problems

Gabriel Missael Barco, Alexandre Adam, Connor Stone +2

Bayesian inference for inverse problems hinges critically on the choice of priors. In the absence of specific prior information, population-level distributions can serve as effecti…

astro-ph.IM2024

Caustics: A Python Package for Accelerated Strong Gravitational Lensing Simulations

Connor Stone, Alexandre Adam, Adam Coogan +9

Gravitational lensing is the deflection of light rays due to the gravity of intervening masses. This phenomenon is observed in a variety of scales and configurations, involving any…