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2020 – today
- 2022
[i7]George Stein, Uros Seljak, Vanessa Böhm, G. Aldering, P. Antilogus, C. Aragon, S. Bailey, C. Baltay, Sébastien Bongard, K. Boone, C. Buton, Y. Copin, S. Dixon, Dominique Fouchez, Emmanuel Gangler, R. Gupta, B. Hayden, W. Hillebrandt, M. Karmen, A. G. Kim, M. Kowalski, D. Kusters, P. F. Leget, F. Mondon, J. Nordin, R. Pain, E. Pecontal, R. Pereira, S. Perlmutter, K. A. Ponder, D. Rabinowitz, M. Rigault, D. Rubin, K. Runge, C. Saunders, G. Smadja, N. Suzuki, C. Tao, Rollin C. Thomas, Maria Vincenzi:
A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series. CoRR abs/2207.07645 (2022)- [i6]Vanessa Böhm, Wei Ji Leong, Ragini Bal Mahesh
, Ioannis Prapas, Edoardo Nemni, Freddie Kalaitzis, Siddha Ganju, Raúl Ramos-Pollán:
Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes. CoRR abs/2211.02869 (2022) - [i5]Vanessa Böhm, Wei Ji Leong, Ragini Bal Mahesh, Ioannis Prapas, Edoardo Nemni, Freddie Kalaitzis, Siddha Ganju, Raúl Ramos-Pollán:
SAR-based landslide classification pretraining leads to better segmentation. CoRR abs/2211.09927 (2022) - 2021
- [j1]Vanessa Böhm, Y. Feng, M. E. Lee, Biwei Dai:
MADLens, a python package for fast and differentiable non-Gaussian lensing simulations. Astron. Comput. 36: 100490 (2021) - 2020
- [i4]Chandan Singh, Wooseok Ha, François Lanusse, Vanessa Böhm, Jia Liu, Bin Yu:
Transformation Importance with Applications to Cosmology. CoRR abs/2003.01926 (2020) - [i3]Vanessa Böhm, Uros Seljak:
Probabilistic Auto-Encoder. CoRR abs/2006.05479 (2020)
2010 – 2019
- 2019
- [i2]Vanessa Böhm, François Lanusse, Uros Seljak:
Uncertainty Quantification with Generative Models. CoRR abs/1910.10046 (2019) - 2014
- [i1]Sebastian Dorn, Torsten A. Enßlin, Maksim Greiner, Marco Selig, Vanessa Böhm:
Signal inference with unknown response: calibration uncertainty renormalized estimator. CoRR abs/1410.6289 (2014)
Coauthor Index
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