activity
20182026
most citedTranslation and Rotation Equivariant Normalizing Flow (TRENF) for Optimal Cosmological Analysis

50 citations · 284 across the 21 of their papers we have counts for

collaborators

21 papers

astro-ph.IM2026

The information content of optical intensity interferometry

Neal Dalal, Biwei Dai, Matthew K. Browning

Optical intensity interferometry (II) can in principle resolve structure on angular scales , but it measures only the squared visibility , discarding Fouri…

astro-ph.CO2026

FAIR Universe Weak Lensing ML Uncertainty Challenge: Handling Uncertainties and Distribution Shifts for Precision Cosmology

Biwei Dai, Po-Wen Chang, Wahid Bhimji +15

Weak gravitational lensing, the correlated distortion of background galaxy shapes by foreground structures, is a powerful probe of the matter distribution in our universe and allow…

cs.AI2026

Competing with AI Scientists: Agent-Driven Approach to Astrophysics Research

Thomas Borrett, Licong Xu, Andy Nilipour +7

We present an agent-driven approach to the construction of parameter inference pipelines for scientific data analysis. Our method leverages a multi-agent system, Cmbagent (the anal…

astro-ph.CO2025

Cosmic Shear constraints from HSC Year 3 with clustering calibration of the tomographic redshift distributions from DESI

J. Choppin de Janvry, B. Dai, S. Gontcho A Gontcho +2

We reanalyze cosmological constraints from Hyper Suprime-Cam (HSC) Y3 shear-shear correlation function using new calibration of the tomographic redshift distribution via the cluste…

astro-ph.CO2025★ 1 cited

One latent to fit them all: a unified representation of baryonic feedback on matter distribution

Shurui Lin, Yin Li, Shy Genel +4

Accurate and parsimonious quantification of baryonic feedback on matter distribution is of crucial importance for understanding both cosmology and galaxy formation from observation…

astro-ph.CO2025★ 2 cited

Detecting Modeling Bias with Continuous Time Flow Models on Weak Lensing Maps

Kangning Diao, Biwei Dai, Uros Seljak

Simulation-based inference provides a powerful framework for extracting rich information from nonlinear scales in current and upcoming cosmological surveys, and ensuring its robust…