33 citations · 74 across the 9 of their papers we have counts for
9 papers
{\sc SimBIG}: Cosmological Constraints using Simulation-Based Inference of Galaxy Clustering with Marked Power Spectra
Elena Massara, ChangHoon Hahn, Michael Eickenberg +7
We present the first CDM cosmological analysis performed on a galaxy survey using marked power spectra. The marked power spectrum is the two-point function of a marked field, wh…
: Cosmological Constraints from the Redshift-Space Galaxy Skew Spectra
Jiamin Hou, Azadeh Moradinezhad Dizgah, ChangHoon Hahn +7
Extracting the non-Gaussian information of the cosmic large-scale structure (LSS) is vital in unlocking the full potential of the rich datasets from the upcoming stage-IV galaxy su…
Reusability report: Prostate cancer stratification with diverse biologically-informed neural architectures
Christian Pedersen, Tiberiu Tesileanu, Tinghui Wu +4
In Elmarakeby et al., "Biologically informed deep neural network for prostate cancer discovery", a feedforward neural network with biologically informed, sparse connections (P-NET)…
SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering
Pablo Lemos, Liam Parker, ChangHoon Hahn +8
We present the first simulation-based inference (SBI) of cosmological parameters from field-level analysis of galaxy clustering. Standard galaxy clustering analyses rely on analyzi…
: The First Cosmological Constraints from Non-Gaussian and Non-Linear Galaxy Clustering
ChangHoon Hahn, Pablo Lemos, Liam Parker +8
The 3D distribution of galaxies encodes detailed cosmological information on the expansion and growth history of the Universe. We present the first cosmological constraints that ex…
: The First Cosmological Constraints from the Non-Linear Galaxy Bispectrum
ChangHoon Hahn, Michael Eickenberg, Shirley Ho +7
We present the first cosmological constraints from analyzing higher-order galaxy clustering on non-linear scales. We use , a forward modeling framework…
Galaxy Clustering Analysis with SimBIG and the Wavelet Scattering Transform
Bruno Régaldo-Saint Blancard, ChangHoon Hahn, Shirley Ho +8
The non-Gaussisan spatial distribution of galaxies traces the large-scale structure of the Universe and therefore constitutes a prime observable to constrain cosmological parameter…
Multiple Physics Pretraining for Physical Surrogate Models
Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Holden Parker +11
We introduce multiple physics pretraining (MPP), an autoregressive task-agnostic pretraining approach for physical surrogate modeling of spatiotemporal systems with transformers. I…
xVal: A Continuous Numerical Tokenization for Scientific Language Models
Siavash Golkar, Mariel Pettee, Michael Eickenberg +11
Due in part to their discontinuous and discrete default encodings for numbers, Large Language Models (LLMs) have not yet been commonly used to process numerically-dense scientific…