David W. Hogg

29 papers A* 3A 1Journal 25
YearRankTypeTitle / Venue / Authors
2025 J jnl
Causal Foundation Models: Disentangling Physics from Instrument Properties.
CoRR
Jeroen Audenaert, Daniel Muthukrishna, Paul F. Gregory, David W. Hogg, V. Ashley Villar
2025 J jnl
Group Averaging for Physics Applications: Accuracy Improvements at Zero Training Cost.
CoRR
Valentino F. Foit, David W. Hogg, Soledad Villar
2025 J jnl
ginjax: E(d)-Equivariant CNN for Tensor Images.
J. Open Source Softw.
Wilson Gregory, Kaze W. K. Wong, David W. Hogg, Soledad Villar
2024 J jnl
Is machine learning good or bad for the natural sciences?
CoRR
David W. Hogg, Soledad Villar
2024 J jnl
NotPlaNET: Removing False Positives from Planet Hunters TESS with Machine Learning.
CoRR
Valentina Tardugno Poleo, Nora Eisner, David W. Hogg
2024 A* conf
Position: Is machine learning good or bad for the natural sciences?
ICML
David W. Hogg, Soledad Villar
2024 J jnl
Towards fully covariant machine learning.
Trans. Mach. Learn. Res.
Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf
2023 J jnl
Dimensionless machine learning: Imposing exact units equivariance.
J. Mach. Learn. Res.
Soledad Villar, Weichi Yao, David W. Hogg, Ben Blum-Smith, Bianca Dumitrascu
2023 J jnl
GeometricImageNet: Extending convolutional neural networks to vector and tensor images.
CoRR
Wilson Gregory, David W. Hogg, Ben Blum-Smith, Maria Teresa Arias, Kaze W. K. Wong, Soledad Villar
2023 J jnl
The passive symmetries of machine learning.
CoRR
Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf
2022 J jnl
Dimensionality Reduction, Regularization, and Generalization in Overparameterized Regressions.
SIAM J. Math. Data Sci.
Ningyuan Teresa Huang, David W. Hogg, Soledad Villar
2022 J jnl
Dimensionless machine learning: Imposing exact units equivariance.
CoRR
Soledad Villar, Weichi Yao, David W. Hogg, Ben Blum-Smith, Bianca Dumitrascu
2021 J jnl
A simple equivariant machine learning method for dynamics based on scalars.
CoRR
Weichi Yao, Kate Storey-Fisher, David W. Hogg, Soledad Villar
2021 J jnl
Fitting very flexible models: Linear regression with large numbers of parameters.
CoRR
David W. Hogg, Soledad Villar
2021 A* conf
Scalars are universal: Equivariant machine learning, structured like classical physics.
NeurIPS
Soledad Villar, David W. Hogg, Kate Storey-Fisher, Weichi Yao, Ben Blum-Smith
2021 J jnl
Scalars are universal: Gauge-equivariant machine learning, structured like classical physics.
CoRR
Soledad Villar, David W. Hogg, Kate Storey-Fisher, Weichi Yao, Ben Blum-Smith
2020 J jnl
Dimensionality reduction, regularization, and generalization in overparameterized regressions.
CoRR
Ningyuan Huang, David W. Hogg, Soledad Villar
2020 J jnl
Maelstrom: A Python package for identifying companions to pulsating stars from their light travel time variations.
J. Open Source Softw.
Daniel Hey, Simon Murphy, Daniel Foreman-Mackey, Timothy Bedding, Benjamin J. S. Pope, David W. Hogg
2019 J jnl
emcee v3: A Python ensemble sampling toolkit for affine-invariant MCMC.
J. Open Source Softw.
Daniel Foreman-Mackey, Will Farr, Manodeep Sinha, Anne M. Archibald, David W. Hogg, Jeremy Sanders, Joe Zuntz, Peter H. Williams, Andrew R. J. Nelson, Miguel de Val-Borro, Tobias Erhardt, Ilya Pashchenko, Oriol Abril Pla
2017 J jnl
Hack Weeks as a model for Data Science Education and Collaboration.
CoRR
Daniela Huppenkothen, Anthony Arendt, David W. Hogg, Karthik Ram, Jake VanderPlas, Ariel Rokem
2016 J jnl
Fast Direct Methods for Gaussian Processes.
IEEE Trans. Pattern Anal. Mach. Intell.
Sivaram Ambikasaran, Daniel Foreman-Mackey, Leslie Greengard, David W. Hogg, Michael O'Neil
2016 J jnl
Modeling confounding by half-sibling regression.
Proc. Natl. Acad. Sci. USA
Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
2015 A* conf
Removing systematic errors for exoplanet search via latent causes.
ICML
Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
2015 J jnl
Removing systematic errors for exoplanet search via latent causes.
CoRR
Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
2014 J jnl
10 Simple Rules for the Care and Feeding of Scientific Data.
CoRR
Alyssa Goodman, Alberto Pepe, Alexander W. Blocker, Christine L. Borgman, Kyle Cranmer, Mercè Crosas, Rosanne Di Stefano, Yolanda Gil, Paul Groth, Margaret L. Hedstrom, David W. Hogg, Vinay L. Kashyap, Ashish Mahabal, Aneta Siemiginowska, Aleksandra B. Slavkovic
2014 J jnl
Ten Simple Rules for the Care and Feeding of Scientific Data.
PLoS Comput. Biol.
Alyssa Goodman, Alberto Pepe, Alexander W. Blocker, Christine L. Borgman, Kyle Cranmer, Mercè Crosas, Rosanne Di Stefano, Yolanda Gil, Paul Groth, Margaret L. Hedstrom, David W. Hogg, Vinay L. Kashyap, Ashish Mahabal, Aneta Siemiginowska, Aleksandra B. Slavkovic
2014 A conf
Towards building a Crowd-Sourced Sky Map.
AISTATS
Dustin Lang, David W. Hogg, Bernhard Schölkopf
2014 J jnl
Towards building a Crowd-Sourced Sky Map.
CoRR
Dustin Lang, David W. Hogg, Bernhard Schölkopf
2008 J jnl
Astronomical imaging: The theory of everything
CoRR
David W. Hogg, Dustin Lang