Low-cost neural summaries for cosmological inference: an ensemble of convolutional neural networks trained on approximate simulations

Machine learning can build near-optimal summary statistics for extracting cosmological information from the large-scale structure of the Universe. Training them, however, requires large numbers of costly simulations. We aim to build a neural summary trained on fast, approximate low-resolution simula