Ashwin Samudre
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View article: nERdy: network analysis of endoplasmic reticulum dynamics
nERdy: network analysis of endoplasmic reticulum dynamics Open
The endoplasmic reticulum (ER) comprises smooth tubules, ribosome-studded sheets, and peripheral sheets that can present as tubular matrices. ER shaping proteins determine ER morphology, however, understanding their role in tubular matrix …
View article: Deep inference of simulated strong lenses in ground-based surveys
Deep inference of simulated strong lenses in ground-based surveys Open
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 dark matter. However, leveraging the increased statistical pow…
View article: Deep inference of simulated strong lenses in ground-based surveys
Deep inference of simulated strong lenses in ground-based surveys Open
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 dark matter. However, leveraging the increased statistical pow…
View article: nERdy: network analysis of endoplasmic reticulum dynamics
nERdy: network analysis of endoplasmic reticulum dynamics Open
The endoplasmic reticulum (ER) comprises smooth tubules, ribosome-studded sheets, and peripheral sheets that can present as tubular matrices. ER shaping proteins determine ER morphology, however, their role in tubular matrix formation requ…
View article: nERdy: network analysis of endoplasmic reticulum dynamics
nERdy: network analysis of endoplasmic reticulum dynamics Open
The endoplasmic reticulum (ER) comprises smooth tubules, ribosome-studded sheets, and peripheral sheets that can present as tubular matrices. ER shaping proteins determine ER morphology, however, understanding their role in tubular matrix …
View article: Comparing Automated Posterior Estimation Techniques for Modeling Strong Lenses In Ground-based Survey Data
Comparing Automated Posterior Estimation Techniques for Modeling Strong Lenses In Ground-based Survey Data Open
Current and future ground-based cosmological surveys, such as the Dark Energy Survey (DES), and the Vera Rubin Observatory Legacy Survey of Space and Time (LSST), are predicted to discover thousands to tens of thousands of strong gravitati…
View article: Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference
Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference Open
galaxy-galaxy lenses. We demonstrate the successful application of Neural Posterior Estimation (NPE) to automate the inference of a 12-parameter lens mass model for DES-like ground-based imaging data. We compare our NPE constraints to a Ba…
View article: Classification of red cell dynamics with convolutional and recurrent neural networks: a sickle cell disease case study
Classification of red cell dynamics with convolutional and recurrent neural networks: a sickle cell disease case study Open
The fraction of red blood cells adopting a specific motion under low shear flow is a promising inexpensive marker for monitoring the clinical status of patients with sickle cell disease. Its high-throughput measurement relies on the video …
View article: Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference
Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference Open
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 the Vera Rubin Observatory Legacy Survey of Space and Time (L…
View article: Data-Efficient Classification of Radio Galaxies
Data-Efficient Classification of Radio Galaxies Open
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 of radio galaxy classification based on morphology using de…
View article: Inferring astrophysical X-ray polarization with deep learning
Inferring astrophysical X-ray polarization with deep learning Open
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 (IXPE), a future NASA selected space-based mission expected to …
View article: Inferring astrophysical X-ray polarization with deep learning
Inferring astrophysical X-ray polarization with deep learning Open
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 (IXPE), a future NASA selected space-based mission expected to …