1.9k citations · 3k across the 24 of their papers we have counts for
25 papers
Do Tabular Foundation Models Know Physics? Contamination, Units, and the Deterministic Limit
Wassim Tenachi, Yashar Hezaveh, Laurence Perreault Levasseur +1
Tabular foundation models (TFMs) learn to fill in tables the way language models fill in text --- and tables are arguably the format in which most physical measurement arrives. Did…
A Fast Generative Framework for High-dimensional Posterior Sampling: Application to CMB Delensing
Hadi Sotoudeh, Pablo Lemos, Laurence Perreault-Levasseur
We introduce a deep generative framework for high-dimensional Bayesian inference that enables efficient posterior sampling. As telescopes and simulations rapidly expand the volume…
Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration
LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz +63
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that cha…
Bridging Simulators with Conditional Optimal Transport
Justine Zeghal, Benjamin Remy, Yashar Hezaveh +2
We propose a new field-level emulator that bridges two simulators using unpaired simulation datasets. Our method leverages a flow-based approach to learn the likelihood transport f…
IRIS: A Bayesian Approach for Image Reconstruction in Radio Interferometry with expressive Score-Based priors
Noé Dia, M. J. Yantovski-Barth, Alexandre Adam +4
Inferring sky surface brightness distributions from noisy interferometric data in a principled statistical framework has been a key challenge in radio astronomy. In this work, we i…
ANDES, the high resolution spectrograph for the ELT: science goals, project overview and future developments
A. Marconi, M. Abreu, V. Adibekyan +286
The first generation of ELT instruments includes an optical-infrared high-resolution spectrograph, indicated as ELT-HIRES and recently christened ANDES (ArmazoNes high Dispersion E…
Tackling the Problem of Distributional Shifts: Correcting Misspecified, High-Dimensional Data-Driven Priors for Inverse Problems
Gabriel Missael Barco, Alexandre Adam, Connor Stone +2
Bayesian inference for inverse problems hinges critically on the choice of priors. In the absence of specific prior information, population-level distributions can serve as effecti…
Strong gravitational lensing as a probe of dark matter
S. Vegetti, S. Birrer, G. Despali +8
Dark matter structures within strong gravitational lens galaxies and along their line of sight leave a gravitational imprint on the multiple images of lensed sources. Strong gravit…
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference
Pablo Lemos, Adam Coogan, Yashar Hezaveh +1
Parameter inference, i.e. inferring the posterior distribution of the parameters of a statistical model given some data, is a central problem to many scientific disciplines. Genera…
Correlated Read Noise Reduction in Infrared Arrays Using Deep Learning
Guillaume Payeur, Étienne Artigau, Laurence Perreault-Levasseur +1
We present a new procedure rooted in deep learning to construct science images from data cubes collected by astronomical instruments using HxRG detectors in low-flux regimes. It im…
Simulation-Based Inference of Strong Gravitational Lensing Parameters
Ronan Legin, Yashar Hezaveh, Laurence Perreault Levasseur +1
In the coming years, a new generation of sky surveys, in particular, Euclid Space Telescope (2022), and the Rubin Observatory's Legacy Survey of Space and Time (LSST, 2023) will di…
Bayesian Neural Networks
Tom Charnock, Laurence Perreault-Levasseur, François Lanusse
In recent times, neural networks have become a powerful tool for the analysis of complex and abstract data models. However, their introduction intrinsically increases our uncertain…
HIGAN: Cosmic Neutral Hydrogen with Generative Adversarial Networks
Juan Zamudio-Fernandez, Atakan Okan, Francisco Villaescusa-Navarro +5
One of the most promising ways to observe the Universe is by detecting the 21cm emission from cosmic neutral hydrogen (HI) through radio-telescopes. Those observations can shed lig…
Data-Driven Reconstruction of Gravitationally Lensed Galaxies using Recurrent Inference Machines
Warren R. Morningstar, Laurence Perreault Levasseur, Yashar D. Hezaveh +6
We present a machine learning method for the reconstruction of the undistorted images of background sources in strongly lensed systems. This method treats the source as a pixelated…
Analyzing interferometric observations of strong gravitational lenses with recurrent and convolutional neural networks
Warren R. Morningstar, Yashar D. Hezaveh, Laurence Perreault Levasseur +4
We use convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to estimate the parameters of strong gravitational lenses from interferometric observations. We exp…
Overview of the DESI Legacy Imaging Surveys
Arjun Dey, David J. Schlegel, Dustin Lang +157
The DESI Legacy Imaging Surveys are a combination of three public projects (the Dark Energy Camera Legacy Survey, the Beijing-Arizona Sky Survey, and the Mayall z-band Legacy Surve…
Fast Automated Analysis of Strong Gravitational Lenses with Convolutional Neural Networks
Yashar D. Hezaveh, Laurence Perreault Levasseur, Philip J. Marshall
Quantifying image distortions caused by strong gravitational lensing and estimating the corresponding matter distribution in lensing galaxies has been primarily performed by maximu…
Detection of lensing substructure using ALMA observations of the dusty galaxy SDP.81
Yashar D. Hezaveh, Neal Dalal, Daniel P. Marrone +13
We study the abundance of substructure in the matter density near galaxies using ALMA Science Verification observations of the strong lensing system SDP.81. We present a method to…
Backreaction and Stochastic Effects in Single Field Inflation
Laurence Perreault Levasseur, Evan McDonough
The formalism of stochastic inflation is a powerful tool for analyzing the backreaction of cosmological perturbations, and making precise predictions for inflationary observables.…
Measuring the power spectrum of dark matter substructure using strong gravitational lensing
Yashar Hezaveh, Neal Dalal, Gilbert Holder +3
In recent years, it has become possible to detect individual dark matter subhalos near images of strongly lensed extended background galaxies. Typically, only the most massive subh…
Recursive Stochastic Effects in Valley Hybrid Inflation
Laurence Perreault Levasseur, Vincent Vennin, Robert Brandenberger
Hybrid Inflation is a two-field model where inflation ends by a tachyonic instability, the duration of which is determined by stochastic effects and has important observational imp…
Lagrangian Formulation of Stochastic Inflation: A Recursive Approach
Laurence Perreault Levasseur
We present a new, recursive approach to stochastic inflation which is self-consistent and solves multiple problems which plagued a certain number of previous studies, in particular…
Defrosting in an Emergent Galileon Cosmology
Laurence Perreault Levasseur, Robert Brandenberger, Anne-Christine Davis
We study the transition from an Emergent Galileon condensate phase of the early universe to a later expanding radiation phase. This "defrosting" or "preheating" transition is a con…
A Matter Bounce By Means of Ghost Condensation
Chunshan Lin, Robert H. Brandenberger, Laurence Perreault Levasseur
Assuming the existence of a scalar field which undergoes "ghost condensation" and which has a suitably chosen potential, it is possible to obtain a non-singular bouncing cosmology…