14 citations · 17 across the 5 of their papers we have counts for
5 papers
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…
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks
Ashwin Samudre, Mircea Petrache, Brian D. Nord +1
There has been much recent interest in designing neural networks (NNs) with relaxed equivariance, which interpolate between exact equivariance and full flexibility for consistent p…
Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference
Jason Poh, Ashwin Samudre, Aleksandra Ćiprijanović +4
Current ground-based cosmological surveys, such as the Dark Energy Survey (DES), are predicted to discover thousands of galaxy-scale strong lenses, while future surveys, such as th…
Data-Efficient Classification of Radio Galaxies
Ashwin Samudre, Lijo George, Mahak Bansal +1
The continuum emission from radio galaxies can be generally classified into different morphological classes such as FRI, FRII, Bent, or Compact. In this paper, we explore the task…
Inferring astrophysical X-ray polarization with deep learning
Nikita Moriakov, Ashwin Samudre, Michela Negro +3
We investigate the use of deep learning in the context of X-ray polarization detection from astrophysical sources as will be observed by the Imaging X-ray Polarimetry Explorer (IXP…