Stars
Benchmarking field-level cosmological inference from galaxy surveys.
Euclid Visible Instrument Python package. Includes a simulator and various analysis codes.
JAX port of GalSim, for parallelized, GPU accelerated, and differentiable galaxy image simulations.
Physically motivated machine learning approach for painting baryons on N-body simulations
A vscode theme generated with pywal color palette
JAX-powered Cosmological Particle-Mesh N-body Solver
A 15TB Collection of Physics Simulation Datasets
Large-Scale Multimodal Dataset of Astronomical Data
Differentiable neuron simulations with biophysical detail on CPU, GPU, or TPU.
Codes associated with the manuscript titled "Multi-stage neural networks: Function approximator of machine precision"
JAX-based linear Einstein-Boltzmann solver for cosmology
PyTorch library for solving imaging inverse problems using deep learning
We build a simulation-based inference framework to estimate the SFHs of galaxies from optical spectra.
JAX-powered Hi-Fi mocks
Multimodal contrastive pretraining for astronomical data
Multi-stage flow-based networks to create N-body halos conditioned on FastPM density
A repository to store state of the art score model architectures
Semantic alignment of astronomical data with natural language using multi-modal models. (Jax) Code associated with https://arxiv.org/abs/2403.08851 (COLM 2023).