3 citations · 7 across the 9 of their papers we have counts for
9 papers
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…
Beyond Point Estimates: Benchmarking Uncertainty Quantification Methods on the AION-1 Astronomical Foundation Model
Karla Tame-Narvaez, Aleksandra Ćiprijanović, Shubhendu Trivedi
Foundation models for astronomical surveys offer powerful learned representations that can be transferred to downstream regression tasks such as galaxy property estimation. However…
Prospects for Astrobiology and Technosignature Searches with the Vera C. Rubin Observatory Legacy Survey of Space and Time
Andjelka B Kovacevic, Nigel J. Mason, Aleksandra Ciprijanovic +5
he Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will repeatedly measure the brightness of billions of astrophysical sources using six colour filters. We test a…
First Estimation of Model Parameters for Neutrino-Induced Nucleon Knockout Using Simulation-Based Inference
Karla Tame-Narvaez, Steven Gardiner, Aleksandra Ćiprijanović +1
To enable an accurate determination of oscillation parameters, accelerator-based neutrino experiments require detailed simulations of nuclear interaction physics in the GeV regime.…
SIDDA: SInkhorn Dynamic Domain Adaptation for Image Classification with Equivariant Neural Networks
Sneh Pandya, Purvik Patel, Brian D. Nord +2
Modern neural networks (NNs) often do not generalize well in the presence of a "covariate shift"; that is, in situations where the training and test data distributions differ, but…
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…
DeepUQ: Assessing the Aleatoric Uncertainties from two Deep Learning Methods
Rebecca Nevin, Aleksandra Ćiprijanović, Brian D. Nord
Assessing the quality of aleatoric uncertainty estimates from uncertainty quantification (UQ) deep learning methods is important in scientific contexts, where uncertainty is physic…
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 (…