66 citations · 78 across the 8 of their papers we have counts for
8 papers
Reconstructing and Classifying SDSS DR16 Galaxy Spectra with Machine-Learning and Dimensionality Reduction Algorithms
Felix Pat, Stéphanie Juneau, Vanessa Böhm +6
Optical spectra of galaxies and quasars from large cosmological surveys are used to measure redshifts and infer distances. They are also rich with information on the intrinsic prop…
Deep learning based landslide density estimation on SAR data for rapid response
Vanessa Boehm, Wei Ji Leong, Ragini Bal Mahesh +5
This work aims to produce landslide density estimates using Synthetic Aperture Radar (SAR) satellite imageries to prioritise emergency resources for rapid response. We use the Unit…
SAR-based landslide classification pretraining leads to better segmentation
Vanessa Böhm, Wei Ji Leong, Ragini Bal Mahesh +5
Rapid assessment after a natural disaster is key for prioritizing emergency resources. In the case of landslides, rapid assessment involves determining the extent of the area affec…
Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes
Vanessa Boehm, Wei Ji Leong, Ragini Bal Mahesh +5
With climate change predicted to increase the likelihood of landslide events, there is a growing need for rapid landslide detection technologies that help inform emergency response…
Impact of COVID-19 on Astronomy: Two Years In
Vanessa Böhm, Jia Liu
We study the impact of the COVID-19 pandemic on astronomy using public records of astronomical publications. We show that COVID-19 has had both positive and negative impacts on res…
MADLens, a python package for fast and differentiable non-Gaussian lensing simulations
Vanessa Böhm, Yu Feng, Max E. Lee +1
We present MADLens a python package for producing non-Gaussian lensing convergence maps at arbitrary source redshifts with unprecedented precision. MADLens is designed to achieve h…
A bias to CMB lensing measurements from the bispectrum of large-scale structure
Vanessa Böhm, Marcel Schmittfull, Blake D. Sherwin
The rapidly improving precision of measurements of gravitational lensing of the Cosmic Microwave Background (CMB) also requires a corresponding increase in the precision of theoret…
Probing the accelerating Universe with radio weak lensing in the JVLA Sky Survey
M. L. Brown, F. B. Abdalla, A. Amara +48
We outline the prospects for performing pioneering radio weak gravitational lensing analyses using observations from a potential forthcoming JVLA Sky Survey program. A large-scale…