Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

Probabilistic Mass Mapping with Neural Score Estimation



Benjamin Remy , Francois Lanusse , Niall Jeffrey , Jia Liu , Jean-Luc Starck , Ken Osato , Tim Schrabback

* Submitted to A&A, 20 pages, 15 figures, comments are welcome 

   Access Paper or Ask Questions

Adaptive wavelet distillation from neural networks through interpretations



Wooseok Ha , Chandan Singh , Francois Lanusse , Eli Song , Song Dang , Kangmin He , Srigokul Upadhyayula , Bin Yu


   Access Paper or Ask Questions

Real-Time Likelihood-Free Inference of Roman Binary Microlensing Events with Amortized Neural Posterior Estimation



Keming Zhang , Joshua S. Bloom , B. Scott Gaudi , Francois Lanusse , Casey Lam , Jessica Lu

* 14 pages, 8 figures, 3 tables. Submitted to AAS journals. This article supersedes arXiv:2010.04156. Minor edits to figures and Section 4.4 

   Access Paper or Ask Questions

Real-Time Likelihood-free Inference of Roman Binary Microlensing Events with Amortized Neural Posterior Estimation



Keming Zhang , Joshua S. Bloom , B. Scott Gaudi , Francois Lanusse , Casey Lam , Jessica Lu

* 14 pages, 8 figures, 3 tables. Submitted to AAS journals. This article supersedes arXiv:2010.04156 

   Access Paper or Ask Questions

Denoising Score-Matching for Uncertainty Quantification in Inverse Problems



Zaccharie Ramzi , Benjamin Remy , Francois Lanusse , Jean-Luc Starck , Philippe Ciuciu


   Access Paper or Ask Questions

Automating Inference of Binary Microlensing Events with Neural Density Estimation



Keming Zhang , Joshua S. Bloom , B. Scott Gaudi , Francois Lanusse , Casey Lam , Jessica Lu

* 7 pages, 1 figure. Submitted to the ML4PS workshop at NeurIPS 2020 

   Access Paper or Ask Questions

Transformation Importance with Applications to Cosmology



Chandan Singh , Wooseok Ha , Francois Lanusse , Vanessa Boehm , Jia Liu , Bin Yu

* Accepted to ICLR 2020 Workshop on Fundamental Science in the era of AI 

   Access Paper or Ask Questions

Hybrid Physical-Deep Learning Model for Astronomical Inverse Problems



Francois Lanusse , Peter Melchior , Fred Moolekamp

* 8 pages, accepted submission to the NeurIPS 2019 Machine Learning and the Physical Sciences Workshop 

   Access Paper or Ask Questions

Enabling Dark Energy Science with Deep Generative Models of Galaxy Images



Siamak Ravanbakhsh , Francois Lanusse , Rachel Mandelbaum , Jeff Schneider , Barnabas Poczos


   Access Paper or Ask Questions