David W. Hogg

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 18

Top Topics

Natural Sciences

Convolutional Neural Networks

Machine Learning

Gaussian Process

Top Venues

J. Open Source Softw.

SIAM J. Math. Data Sci.

Publications

Valentina Tardugno Poleo, Nora Eisner, David W. Hogg
NotPlaNET: Removing False Positives from Planet Hunters TESS with Machine Learning. CoRR (2024)
Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf
Towards fully covariant machine learning. Trans. Mach. Learn. Res. 2024 (2024)
David W. Hogg, Soledad Villar
Is machine learning good or bad for the natural sciences? CoRR (2024)
Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf
The passive symmetries of machine learning. CoRR (2023)
Wilson Gregory, David W. Hogg, Ben Blum-Smith, Maria Teresa Arias, Kaze W. K. Wong, Soledad Villar
GeometricImageNet: Extending convolutional neural networks to vector and tensor images. CoRR (2023)
Soledad Villar, Weichi Yao, David W. Hogg, Ben Blum-Smith, Bianca Dumitrascu
Dimensionless machine learning: Imposing exact units equivariance. J. Mach. Learn. Res. 24 (2023)
Soledad Villar, Weichi Yao, David W. Hogg, Ben Blum-Smith, Bianca Dumitrascu
Dimensionless machine learning: Imposing exact units equivariance. CoRR (2022)
Ningyuan Teresa Huang, David W. Hogg, Soledad Villar
Dimensionality Reduction, Regularization, and Generalization in Overparameterized Regressions. SIAM J. Math. Data Sci. 4 (1) (2022)
Soledad Villar, David W. Hogg, Kate Storey-Fisher, Weichi Yao, Ben Blum-Smith
Scalars are universal: Equivariant machine learning, structured like classical physics. NeurIPS (2021)
Weichi Yao, Kate Storey-Fisher, David W. Hogg, Soledad Villar
A simple equivariant machine learning method for dynamics based on scalars. CoRR (2021)
Soledad Villar, David W. Hogg, Kate Storey-Fisher, Weichi Yao, Ben Blum-Smith
Scalars are universal: Gauge-equivariant machine learning, structured like classical physics. CoRR (2021)
David W. Hogg, Soledad Villar
Fitting very flexible models: Linear regression with large numbers of parameters. CoRR (2021)
Ningyuan Huang, David W. Hogg, Soledad Villar
Dimensionality reduction, regularization, and generalization in overparameterized regressions. CoRR (2020)
Daniel Hey, Simon Murphy, Daniel Foreman-Mackey, Timothy Bedding, Benjamin Pope, David W. Hogg
Maelstrom: A Python package for identifying companions to pulsating stars from their light travel time variations. J. Open Source Softw. 5 (51) (2020)
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
emcee v3: A Python ensemble sampling toolkit for affine-invariant MCMC. J. Open Source Softw. 4 (43) (2019)
Daniela Huppenkothen, Anthony Arendt, David W. Hogg, Karthik Ram, Jake VanderPlas, Ariel Rokem
Hack Weeks as a model for Data Science Education and Collaboration. CoRR (2017)
Sivaram Ambikasaran, Daniel Foreman-Mackey, Leslie Greengard, David W. Hogg, Michael O'Neil
Fast Direct Methods for Gaussian Processes. IEEE Trans. Pattern Anal. Mach. Intell. 38 (2) (2016)
Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
Modeling confounding by half-sibling regression. Proc. Natl. Acad. Sci. USA 113 (27) (2016)
Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
Removing systematic errors for exoplanet search via latent causes. ICML (2015)
Bernhard Schölkopf, David W. Hogg, Dun Wang, Daniel Foreman-Mackey, Dominik Janzing, Carl-Johann Simon-Gabriel, Jonas Peters
Removing systematic errors for exoplanet search via latent causes. CoRR (2015)
Dustin Lang, David W. Hogg, Bernhard Schölkopf
Towards building a Crowd-Sourced Sky Map. CoRR (2014)
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 Kashyap, Ashish Mahabal, Aneta Siemiginowska, Aleksandra B. Slavkovic
Ten Simple Rules for the Care and Feeding of Scientific Data. PLoS Comput. Biol. 10 (4) (2014)
Dustin Lang, David W. Hogg, Bernhard Schölkopf
Towards building a Crowd-Sourced Sky Map. AISTATS (2014)
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 Kashyap, Ashish Mahabal, Aneta Siemiginowska, Aleksandra B. Slavkovic
10 Simple Rules for the Care and Feeding of Scientific Data. CoRR (2014)
David W. Hogg, Dustin Lang
Astronomical imaging: The theory of everything CoRR (2008)