6 citations · 11 across the 8 of their papers we have counts for
8 papers
Differentiable Stochastic Halo Occupation Distribution with Galaxy Intrinsic Alignments
Sneh Pandya, Jonathan Blazek
We present diffHOD-IA, a fully differentiable implementation of a halo occupation distribution (HOD) model that incorporates galaxy intrinsic alignments (IA). Motivated by the diff…
On Soft Clustering For Correlation Estimators
Edward Berman, Sneh Pandya, Jacqueline McCleary +14
Properly estimating correlations between objects at different spatial scales necessitates distance calculations. For this reason, most widely adopted packages fo…
IAEmu: Learning Galaxy Intrinsic Alignment Correlations
Sneh Pandya, Yuanyuan Yang, Nicholas Van Alfen +2
The intrinsic alignments (IA) of galaxies, a key contaminant in weak lensing analyses, arise from correlations in galaxy shapes driven by tidal interactions and galaxy formation pr…
Building Machine Learning Challenges for Anomaly Detection in Science
Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova +148
Scientific discoveries are often made by finding a pattern or object that was not predicted by the known rules of science. Oftentimes, these anomalous events or objects that do not…
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…
On the Generality and Persistence of Cosmological Stasis
James Halverson, Sneh Pandya
Hierarchical decays of matter species to radiation may balance against Hubble expansion to yield stasis, a new phase of cosmological evolution with constant matter and radiatio…
Learning Galaxy Intrinsic Alignment Correlations
Sneh Pandya, Yuanyuan Yang, Nicholas Van Alfen +2
The intrinsic alignments (IA) of galaxies, regarded as a contaminant in weak lensing analyses, represents the correlation of galaxy shapes due to gravitational tidal interactions a…
E(2) Equivariant Neural Networks for Robust Galaxy Morphology Classification
Sneh Pandya, Purvik Patel, Franc O +1
We propose the use of group convolutional neural network architectures (GCNNs) equivariant to the 2D Euclidean group, , for the task of galaxy morphology classification by ut…