Phil Marshall

Phil Marshall

Stanford University

H-index: 77

North America-United States

About Phil Marshall

Phil Marshall, With an exceptional h-index of 77 and a recent h-index of 55 (since 2020), a distinguished researcher at Stanford University, specializes in the field of astrophysics, cosmology, inference.

His recent articles reflect a diverse array of research interests and contributions to the field:

A Bayesian approach to strong lens finding in the era of wide-area surveys

Image deconvolution and PSF reconstruction with STARRED: a wavelet-based two-channel method optimized for light curve extraction

Expected Lens Model Parameter Accuracy in the LSST Lensed AGN Sample

Rubin/LSST In-kind Contribution Program Produces Mutual Benefits

Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks

An HST Gap Program for lensed Quasars

From images to dark matter: End-to-end inference of substructure from hundreds of strong gravitational lenses

VizieR Online Data Catalog: Galaxies and groups around the WFI 2033-4723 lens (Sluse+, 2019)

Phil Marshall Information

University

Position

SLAC National Accelerator Laboratory

Citations(all)

23859

Citations(since 2020)

13179

Cited By

16272

hIndex(all)

77

hIndex(since 2020)

55

i10Index(all)

191

i10Index(since 2020)

145

Email

University Profile Page

Stanford University

Google Scholar

View Google Scholar Profile

Phil Marshall Skills & Research Interests

astrophysics

cosmology

inference

Top articles of Phil Marshall

Title

Journal

Author(s)

Publication Date

A Bayesian approach to strong lens finding in the era of wide-area surveys

Monthly Notices of the Royal Astronomical Society

Philip Holloway

Philip J Marshall

Aprajita Verma

Anupreeta More

Raoul Cañameras

...

2024/5

Image deconvolution and PSF reconstruction with STARRED: a wavelet-based two-channel method optimized for light curve extraction

arXiv preprint arXiv:2402.08725

Martin Millon

Kevin Michalewicz

Frédéric Dux

Frédéric Courbin

Philip J Marshall

2024/2/13

Expected Lens Model Parameter Accuracy in the LSST Lensed AGN Sample

American Astronomical Society Meeting Abstracts

Padma Venkatraman

Sydney Erickson

Philip Marshall

2024/2

Rubin/LSST In-kind Contribution Program Produces Mutual Benefits

The NOIRLab Mirror

B Blum

P Marshall

K Metzger

A Verma

2024/1

Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks

The Astrophysical Journal

Ji Won Park

Simon Birrer

Madison Ueland

Miles Cranmer

Adriano Agnello

...

2023/8/16

An HST Gap Program for lensed Quasars

HST Proposal

Cameron Lemon

Adriano Agnello

Timo Anguita

Frederic Courbin

Philip J Marshall

...

2023/5

From images to dark matter: End-to-end inference of substructure from hundreds of strong gravitational lenses

The Astrophysical Journal

Sebastian Wagner-Carena

Jelle Aalbers

Simon Birrer

Ethan O Nadler

Elise Darragh-Ford

...

2023/1/13

VizieR Online Data Catalog: Galaxies and groups around the WFI 2033-4723 lens (Sluse+, 2019)

VizieR Online Data Catalog

D Sluse

CE Rusu

CD Fassnacht

A Sonnenfeld

J Richard

...

2023/1

On the detectability of strong lensing in near-infrared surveys

Monthly Notices of the Royal Astronomical Society

Philip Holloway

Aprajita Verma

Philip J Marshall

Anupreeta More

Matthias Tecza

2023/10

Waves Across the South: A New History of Revolution and Empire, by Sujit Sivasundaram

PJ Marshall

2022/8/1

Strong lensing time-delay cosmography in the 2020s

Tommaso Treu

Sherry H Suyu

Philip J Marshall

2022/12

British Traders in the East Indies, 1770–1820:‘At Home in the Eastern Seas’, by WG Miller

PJ Marshall

2022/2/1

The Global Indies: British Imperial Culture and the Reshaping of the World, 1756–1815, by Ashley Cohen

PJ Marshall

2022/6/1

baobab: Training data generator for hierarchically modeling strong lenses with Bayesian neural networks

Astrophysics Source Code Library

Ji Won Park

Sebastian Wagner-Carena

Simon Birrer

Philip J Marshall

Joshua Yao-Yu Lin

...

2022/11

Rubin-Euclid Derived Data Products: Initial Recommendations

arXiv preprint arXiv:2201.03862

Leanne P Guy

Jean-Charles Cuillandre

Etienne Bachelet

Manda Banerji

Franz E Bauer

...

2022/1/11

Glyndwr Williams (1932–2022)

PJ Marshall

2022/5/4

ovejero: Bayesian neural network inference of strong gravitational lenses

Astrophysics Source Code Library

Sebastian Wagner-Carena

Ji Won Park

Simon Birrer

Philip J Marshall

Aaron Roodman

...

2022/11

lsst/rubin_sim: 0.12. 1

Zenodo

Peter Yoachim

R Lynne Jones

Eric H Neilsen

Tiago Ribeiro

Scott Daniel

...

2022

The impact of observing strategy on cosmological constraints with LSST

The Astrophysical Journal Supplement Series

Michelle Lochner

Dan Scolnic

Husni Almoubayyed

Timo Anguita

Humna Awan

...

2022/4/6

paltas: Simulation-based inference on strong gravitational lensing systems

Astrophysics Source Code Library

Sebastian Wagner-Carena

Jelle Aalbers

Simon Birrer

Ethan O Nadler

Elise Darragh-Ford

...

2022/10

See List of Professors in Phil Marshall University(Stanford University)

Co-Authors

H-index: 139
Jean-Paul KNEIB

Jean-Paul KNEIB

École Polytechnique Fédérale de Lausanne

H-index: 117
David W Hogg

David W Hogg

New York University

H-index: 72
Chris Fassnacht

Chris Fassnacht

University of California, Davis

H-index: 36
Brendon J. Brewer

Brendon J. Brewer

University of Auckland

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