Search Results for author: François Lanusse

Found 6 papers, 4 papers with code

Neural Posterior Estimation with Differentiable Simulators

no code implementations12 Jul 2022 Justine Zeghal, François Lanusse, Alexandre Boucaud, Benjamin Remy, Eric Aubourg

Simulation-Based Inference (SBI) is a promising Bayesian inference framework that alleviates the need for analytic likelihoods to estimate posterior distributions.

Bayesian Inference Density Estimation +1

Hybrid Physical-Neural ODEs for Fast N-body Simulations

1 code implementation12 Jul 2022 Denise Lanzieri, François Lanusse, Jean-Luc Starck

We present a new scheme to compensate for the small-scales approximations resulting from Particle-Mesh (PM) schemes for cosmological N-body simulations.

Bayesian Neural Networks

no code implementations2 Jun 2020 Tom Charnock, Laurence Perreault-Levasseur, François Lanusse

In recent times, neural networks have become a powerful tool for the analysis of complex and abstract data models.

Uncertainty Quantification with Generative Models

1 code implementation22 Oct 2019 Vanessa Böhm, François Lanusse, Uroš Seljak

We develop a generative model-based approach to Bayesian inverse problems, such as image reconstruction from noisy and incomplete images.

Image Reconstruction

Deep learning dark matter map reconstructions from DES SV weak lensing data

2 code implementations1 Aug 2019 Niall Jeffrey, François Lanusse, Ofer Lahav, Jean-Luc Starck

With a validation set of 8000 simulated DES SV data realisations, compared to Wiener filtering with a fixed power spectrum, the DeepMass method improved the mean-square-error (MSE) by 11 per cent.

Cosmology and Nongalactic Astrophysics

Cannot find the paper you are looking for? You can Submit a new open access paper.