Publications (10)
Denoising Score-Matching for Uncertainty Quantification in Inverse Problems
Zaccharie Ramzi, Benjamin Remy, Francois Lanusse +2
Deep neural networks have proven extremely efficient at solving a wide rangeof inverse problems, but most often the uncertainty on the solution they provideis hard to quantify. In…
Probabilistic Mass Mapping with Neural Score Estimation
Benjamin Remy, Francois Lanusse, Niall Jeffrey +4
Weak lensing mass-mapping is a useful tool to access the full distribution of dark matter on the sky, but because of intrinsic galaxy ellipticies and finite fields/missing data, th…
Probabilistic Mapping of Dark Matter by Neural Score Matching
Benjamin Remy, Francois Lanusse, Zaccharie Ramzi +3
The Dark Matter present in the Large-Scale Structure of the Universe is invisible, but its presence can be inferred through the small gravitational lensing effect it has on the ima…
Joint inference of weak lensing convergence map and cosmology with diffusion models
Benjamin Remy, Chihway Chang, Rebecca Willett
We present a method for joint inference of cosmological parameters and convergence maps from weak lensing observations, targeting the full posterior conditioned on the observed she…
Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration
LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz +63
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that cha…
Neural Posterior Estimation with Differentiable Simulators
Justine Zeghal, François Lanusse, Alexandre Boucaud +2
Simulation-Based Inference (SBI) is a promising Bayesian inference framework that alleviates the need for analytic likelihoods to estimate posterior distributions. Recent advances…
Disentangling transients and their host galaxies with Scarlet2: A framework to forward model multi-epoch imaging
Charlotte Ward, Peter Melchior, Matt L. Sampson +6
Many science cases for wide-field time-domain surveys rely on accurate identification and characterization of the galaxies hosting transient and variable objects. In the era of the…
A convolutional model for estimating the junction temperatures of SiC MOSFET transistors
Ali El Arabi, Denis Maillet, Nicolas Blet +1
The junction temperature is a very important parameter for monitoring power electronics converters based on MOSFET transistors. They offer the possibility of switching at relativel…
Towards solving model bias in cosmic shear forward modeling
Benjamin Remy, Francois Lanusse, Jean-Luc Starck
As the volume and quality of modern galaxy surveys increase, so does the difficulty of measuring the cosmological signal imprinted in galaxy shapes. Weak gravitational lensing sour…
Bridging Simulators with Conditional Optimal Transport
Justine Zeghal, Benjamin Remy, Yashar Hezaveh +2
We propose a new field-level emulator that bridges two simulators using unpaired simulation datasets. Our method leverages a flow-based approach to learn the likelihood transport f…