18 citations · 25 across the 9 of their papers we have counts for
4 papers · 1 filter
Strong Lensing Cosmology with Population-level Calibrated Neural Ratio Estimation
Sreevani Jarugula, Brian D. Nord, Aleksandra Ćiprijanović +1
Strong gravitational lensing contains key information about cosmic acceleration. Modern and next-generation galaxy imaging surveys are expected to provide high-quality data on $\ma…
Deep inference of simulated strong lenses in ground-based surveys
Jason Poh, Ashwin Samudre, Aleksandra Ćiprijanović +3
The large number of strong lenses discoverable in future astronomical surveys will likely enhance the value of strong gravitational lensing as a cosmic probe of dark energy and dar…
Neural Network Prediction of Strong Lensing Systems with Domain Adaptation and Uncertainty Quantification
Shrihan Agarwal, Aleksandra Ćiprijanović, Brian D. Nord
Modeling strong gravitational lenses is computationally expensive for the complex data from modern and next-generation cosmic surveys. Deep learning has emerged as a promising appr…
Domain-Adaptive Neural Posterior Estimation for Strong Gravitational Lens Analysis
Paxson Swierc, Marcos Tamargo-Arizmendi, Aleksandra Ćiprijanović +1
Modeling strong gravitational lenses is prohibitively expensive for modern and next-generation cosmic survey data. Neural posterior estimation (NPE), a simulation-based inference (…