Sebastian J. Vollmer

According to our database, Sebastian J. Vollmer authored at least 27 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Comparison of causal forest and regression-based approaches to evaluate treatment effect heterogeneity: an application for type 2 diabetes precision medicine.

Ashwini Venkatasubramaniam, Bilal A. Mateen, Beverley M. Shields, Andrew T. Hattersley, Angus G. Jones, Sebastian J. Vollmer, John M. Dennis

BMC Medical Informatics Decis. Mak., December, 2023

Fairness Audits and Debiasing Using \pkg{mlr3fairness}.

Florian Pfisterer, Siyi Wei, Sebastian J. Vollmer, Michel Lang, Bernd Bischl

R J., March, 2023

Energy Discrepancies: A Score-Independent Loss for Energy-Based Models.

Tobias Schröder, Zijing Ou, Jen Ning Lim, Yingzhen Li, Sebastian J. Vollmer, Andrew B. Duncan

CoRR, 2023

Energy Discrepancies: A Score-Independent Loss for Energy-Based Models.

Tobias Schröder, Zijing Ou, Jen Lim, Yingzhen Li, Sebastian J. Vollmer, Andrew Duncan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Energy-Based Models for Functional Data using Path Measure Tilting.

Jen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew Duncan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Flexible Group Fairness Metrics for Survival Analysis.

Raphael Sonabend, Florian Pfisterer, Alan Mishler, Moritz Schauer, Lukas Burk, Sebastian J. Vollmer

CoRR, 2022

F-EBM: Energy Based Learning of Functional Data.

Jen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew Duncan

CoRR, 2022

Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures.

Raphael Sonabend, Andreas Bender, Sebastian J. Vollmer

Bioinform., 2022

Mitigating statistical bias within differentially private synthetic data.

Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Evaluation of survival distribution predictions with discrimination measures.

Raphael Sonabend, Andreas Bender, Sebastian J. Vollmer

CoRR, 2021

Bias Mitigated Learning from Differentially Private Synthetic Data: A Cautionary Tale.

Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes

CoRR, 2021

Foundations of Bayesian Learning from Synthetic Data.

Harrison Wilde, Jack Jewson, Sebastian J. Vollmer, Chris C. Holmes

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Model updating after interventions paradoxically introduces bias.

James Liley, Samuel R. Emerson, Bilal A. Mateen, Catalina A. Vallejos, Louis J. M. Aslett, Sebastian J. Vollmer

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations.

Michael B. Giles, Mateusz B. Majka, Lukasz Szpruch, Sebastian J. Vollmer, Konstantinos C. Zygalakis

Stat. Comput., 2020

Improving the quality of machine learning in health applications and clinical research.

Bilal A. Mateen, James Liley, Alastair K. Denniston, Chris C. Holmes, Sebastian J. Vollmer

Nat. Mach. Intell., 2020

MLJ: A Julia package for composable machine learning.

Anthony D. Blaom, Franz J. Király, Thibaut Liénart, Yiannis Simillides, Diego Arenas, Sebastian J. Vollmer

J. Open Source Softw., 2020

Flexible model composition in machine learning and its implementation in MLJ.

Anthony D. Blaom, Sebastian J. Vollmer

CoRR, 2020

Debiasing classifiers: is reality at variance with expectation?

Ashrya Agrawal, Florian Pfisterer, Bernd Bischl, Jiahao Chen, Srijan Sood, Sameena Shah, Francois Buet-Golfouse, Bilal A. Mateen, Sebastian J. Vollmer

CoRR, 2020

2019

Design choices for productive, secure, data-intensive research at scale in the cloud.

Diego Arenas, Jon Atkins, Clare Austin, David Beavan, Alvaro Cabrejas Egea, Stephen Carlysle-Davies, Ian Carter, Rob Clarke, James Cunningham, Tom Doel, Oliver Forrest, Evelina Gabasova, James Geddes, James Hetherington, Radka Jersakova, Franz J. Király, Catherine Lawrence, Jules Manser, Martin T. O'Reilly, James Robinson, Helen Sherwood-Taylor, Serena Tierney, Catalina A. Vallejos, Sebastian J. Vollmer, Kirstie J. Whitaker

CoRR, 2019

2018

Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness.

Sebastian J. Vollmer, Bilal A. Mateen, Gergo Bohner, Franz J. Király, Rayid Ghani, Pall Jonsson, Sarah Cumbers, Adrian Jonas, Katherine S. L. McAllister, Puja Myles, David Granger, Mark Birse, Richard Branson, Karel G. M. Moons, Gary S. Collins, John P. A. Ioannidis, Chris C. Holmes, Harry Hemingway

CoRR, 2018

2017

Multilevel Monte Carlo for Reliability Theory.

Louis J. M. Aslett, Tigran Nagapetyan, Sebastian J. Vollmer

Reliab. Eng. Syst. Saf., 2017

Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server.

Leonard Hasenclever, Stefan Webb, Thibaut Liénart, Sebastian J. Vollmer, Balaji Lakshminarayanan, Charles Blundell, Yee Whye Teh

J. Mach. Learn. Res., 2017

Relativistic Monte Carlo.

Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever, Yee Whye Teh, Sebastian J. Vollmer

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Exploration of the (Non-)Asymptotic Bias and Variance of Stochastic Gradient Langevin Dynamics.

Sebastian J. Vollmer, Konstantinos C. Zygalakis, Yee Whye Teh

J. Mach. Learn. Res., 2016

Consistency and Fluctuations For Stochastic Gradient Langevin Dynamics.

Yee Whye Teh, Alexandre H. Thiéry, Sebastian J. Vollmer

J. Mach. Learn. Res., 2016

Measuring Sample Quality with Diffusions.

Jack Gorham, Andrew B. Duncan, Sebastian J. Vollmer, Lester W. Mackey

CoRR, 2016

2015

Dimension-Independent MCMC Sampling for Inverse Problems with Non-Gaussian Priors.

Sebastian J. Vollmer

SIAM/ASA J. Uncertain. Quantification, 2015