28 citations · 78 across the 9 of their papers we have counts for
4 papers · 1 filter
Sensitivity Analysis of Simulation-Based Inference for Galaxy Clustering
Chirag Modi, Shivam Pandey, Matthew Ho +3
Simulation-based inference (SBI) is a promising approach to leverage high fidelity cosmological simulations and extract information from the non-Gaussian, non-linear scales that ca…
Information-Ordered Bottlenecks for Adaptive Semantic Compression
Matthew Ho, Xiaosheng Zhao, Benjamin Wandelt
We present the information-ordered bottleneck (IOB), a neural layer designed to adaptively compress data into latent variables ordered by likelihood maximization. Without retrainin…
Posterior Sampling of the Initial Conditions of the Universe from Non-linear Large Scale Structures using Score-Based Generative Models
Ronan Legin, Matthew Ho, Pablo Lemos +4
Reconstructing the initial conditions of the universe is a key problem in cosmology. Methods based on simulating the forward evolution of the universe have provided a way to infer…
Benchmarks and Explanations for Deep Learning Estimates of X-ray Galaxy Cluster Masses
Matthew Ho, John Soltis, Arya Farahi +3
We evaluate the effectiveness of deep learning (DL) models for reconstructing the masses of galaxy clusters using X-ray photometry data from next-generation surveys. We establish t…