Search Results for author:
Found 6 papers, 4 papers with code
Hybrid Physical-Neural ODEs for Fast N-body Simulations
We present a new scheme to compensate for the small-scales approximations resulting from Particle-Mesh (PM) schemes for cosmological N-body simulations.
Neural Posterior Estimation with Differentiable Simulators
Simulation-Based Inference (SBI) is a promising Bayesian inference framework that alleviates the need for analytic likelihoods to estimate posterior distributions.
Bayesian Neural Networks
In recent times, neural networks have become a powerful tool for the analysis of complex and abstract data models.
Uncertainty Quantification with Generative Models
We develop a generative model-based approach to Bayesian inverse problems, such as image reconstruction from noisy and incomplete images.
Deep learning dark matter map reconstructions from DES SV weak lensing data
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
DESCQA: An Automated Validation Framework for Synthetic Sky Catalogs
The use of high-quality simulated sky catalogs is essential for the success of cosmological surveys.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics
