49 citations · 70 across the 4 of their papers we have counts for
4 papers
Teaching dark matter simulations to speak the halo language
Shivam Pandey, Francois Lanusse, Chirag Modi +1
We develop a transformer-based conditional generative model for discrete point objects and their properties. We use it to build a model for populating cosmological simulations with…
Differentiable Stochastic Halo Occupation Distribution
Benjamin Horowitz, ChangHoon Hahn, Francois Lanusse +2
In this work, we demonstrate how differentiable stochastic sampling techniques developed in the context of deep Reinforcement Learning can be used to perform efficient parameter in…
FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver
Chirag Modi, Francois Lanusse, Uros Seljak
We present FlowPM, a Particle-Mesh (PM) cosmological N-body code implemented in Mesh-TensorFlow for GPU-accelerated, distributed, and differentiable simulations. We implement and v…
Uncertainty Quantification with Generative Models
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. Our framework addresses two common challen…