Signal inference with unknown response: calibration uncertainty renormalized estimator. - Sebastian Dorn; Torsten A. Enßlin; Maksim Greiner; Marco Selig; Vanessa Böhm (CoRR, 2014)

Uncertainty Quantification with Generative Models. - Vanessa Böhm; François Lanusse; Uros Seljak (CoRR, 2019)

Transformation Importance with Applications to Cosmology. - Chandan Singh; Wooseok Ha; François Lanusse; Vanessa Böhm; Jia Liu; Bin Yu 001 (CoRR, 2020)

Probabilistic Auto-Encoder. - Vanessa Böhm; Uros Seljak (CoRR, 2020)

MADLens, a python package for fast and differentiable non-Gaussian lensing simulations. - Vanessa Böhm; Y. Feng; M. E. Lee; Biwei Dai (Astron. Comput., 2021)

A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series. - George Stein; Uros Seljak; Vanessa Böhm; G. Aldering; P. Antilogus; C. Aragon; S. Bailey; C. Baltay; Sébastien Bongard; K. Boone; C. Buton; Y. Copin; et al. (CoRR, 2022)

Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes. - Vanessa Böhm; Wei Ji Leong; Ragini Bal Mahesh; Ioannis Prapas; Edoardo Nemni; Freddie Kalaitzis; Siddha Ganju; Raúl Ramos-Pollán (CoRR, 2022)

SAR-based landslide classification pretraining leads to better segmentation. - Vanessa Böhm; Wei Ji Leong; Ragini Bal Mahesh; Ioannis Prapas; Edoardo Nemni; Freddie Kalaitzis; Siddha Ganju; Raúl Ramos-Pollán (CoRR, 2022)