Sebastian J. Vollmer

According to our database, Sebastian J. Vollmer authored at least 54 papers between 2015 and 2025.

Collaborative distances:

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

2025

Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems.

Jan Tauberschmidt, Sophie Fellenz, Sebastian J. Vollmer, Andrew B. Duncan

CoRR, August, 2025

Automated Visualization Makeovers with LLMs.

Siddharth Gangwar, David Antony Selby, Sebastian J. Vollmer

CoRR, August, 2025

BioDisco: Multi-agent hypothesis generation with dual-mode evidence, iterative feedback and temporal evaluation.

Yujing Ke, Kevin George, Kathan Pandya, David Blumenthal, Maximilian Sprang, Gerrit Großmann, Sebastian J. Vollmer, David Antony Selby

CoRR, August, 2025

Exploring the Alignment of Perceived and Measured Sleep Quality with Working Memory using Consumer Wearables.

Peter Neigel, David Antony Selby, Shota Arai, Benjamin Tag, Niels van Berkel, Sebastian J. Vollmer, Andrew Vargo, Koichi Kise

CoRR, July, 2025

Finding Common Ground: Using Large Language Models to Detect Agreement in Multi-Agent Decision Conferences.

Selina Heller, Mohamed Ibrahim, David Antony Selby, Sebastian J. Vollmer

CoRR, July, 2025

FOLC-Net: A Federated-Optimized Lightweight Architecture for Enhanced MRI Disease Diagnosis across Axial, Coronal, and Sagittal Views.

Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian J. Vollmer, Andreas Dengel

CoRR, July, 2025

IMAGIC-500: IMputation benchmark on A Generative Imaginary Country (500k samples).

Siyi Sun, David Antony Selby, Yunchuan Huang, Sebastian J. Vollmer, Seth R. Flaxman, Anisoara Calinescu

CoRR, June, 2025

Robust & Precise Knowledge Distillation-based Novel Context-Aware Predictor for Disease Detection in Brain and Gastrointestinal.

Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian J. Vollmer, Andreas Dengel

CoRR, May, 2025

The Power of Stories: Narrative Priming Shapes How LLM Agents Collaborate and Compete.

Gerrit Großmann, Larisa Ivanova, Sai Leela Poduru, Mohaddeseh Tabrizian, Islam Mesabah, David Antony Selby, Sebastian J. Vollmer

CoRR, May, 2025

When Counterfactual Reasoning Fails: Chaos and Real-World Complexity.

Yahya Aalaila, Gerrit Großmann, Sumantrak Mukherjee, Jonas Wahl, Sebastian J. Vollmer

CoRR, March, 2025

AI-Driven Diabetic Retinopathy Diagnosis Enhancement through Image Processing and Salp Swarm Algorithm-Optimized Ensemble Network.

Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian J. Vollmer, Andreas Dengel

CoRR, March, 2025

Neural Spatiotemporal Point Processes: Trends and Challenges.

Sumantrak Mukherjee, Mouad Elhamdi, George Mohler, David Antony Selby, Yao Xie, Sebastian J. Vollmer, Gerrit Grossmann

CoRR, February, 2025

CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning.

Yousef Koka, David Antony Selby, Gerrit Großmann, Sebastian J. Vollmer

CoRR, February, 2025

Visible neural networks for multi-omics integration: a critical review.

David Antony Selby, Rashika Jakhmola, Maximilian Sprang, Gerrit Großmann, Hind Raki, Niloofar Maani, Daria Pavliuk, Jan Ewald, Sebastian J. Vollmer

Frontiers Artif. Intell., 2025

Rethinking Cancer Gene Identification Through Graph Anomaly Analysis.

Yilong Zang, Lingfei Ren, Yue Li, Zhikang Wang, David Antony Selby, Zheng Wang, Sebastian Josef Vollmer, Hongzhi Yin, Jiangning Song, Junhang Wu

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Development and assessment of a machine learning tool for predicting emergency admission in Scotland.

James Liley, Gergo Bohner, Samuel R. Emerson, Bilal A. Mateen, Katie Borland, David Carr, Scott Heald, Samuel D. Oduro, Jill Ireland, Keith Moffat, Rachel Porteous, Stephen Riddell, Simon Rogers, Ioanna Thoma, Nathan Cunningham, Chris Holmes, Katrina Payne, Sebastian J. Vollmer, Catalina A. Vallejos, Louis J. M. Aslett

npj Digit. Medicine, 2024

Publisher Correction: Development and assessment of a machine learning tool for predicting emergency admission in Scotland.

James Liley, Gergo Bohner, Samuel R. Emerson, Bilal A. Mateen, Katie Borland, David Carr, Scott Heald, Samuel D. Oduro, Jill Ireland, Keith Moffat, Rachel Porteous, Stephen Riddell, Simon Rogers, Ioanna Thoma, Nathan Cunningham, Chris Holmes, Katrina Payne, Sebastian J. Vollmer, Catalina A. Vallejos, Louis J. M. Aslett

npj Digit. Medicine, 2024

Survival prediction landscape: an in-depth systematic literature review on activities, methods, tools, diseases, and databases.

Ahtisham Fazeel Abbasi, Muhammad Nabeel Asim, Sheraz Ahmed, Sebastian J. Vollmer, Andreas Dengel

Frontiers Artif. Intell., 2024

Graph Agnostic Causal Bayesian Optimisation.

Sumantrak Mukherjee, Mengyan Zhang, Seth R. Flaxman, Sebastian J. Vollmer

CoRR, 2024

icon: Fast Simulation of Epidemics on Coevolving Networks.

Gerrit Großmann, Sebastian J. Vollmer

CoRR, 2024

Act as a Honeytoken Generator! An Investigation into Honeytoken Generation with Large Language Models.

Daniel Reti, Norman Becker, Tillmann Angeli, Anasuya Chattopadhyay, Daniel Schneider, Sebastian J. Vollmer, Hans D. Schotten

CoRR, 2024

Quantitative knowledge retrieval from large language models.

David Antony Selby, Kai Spriestersbach, Yuichiro Iwashita, Dennis Bappert, Archana Warrier, Sumantrak Mukherjee, Muhammad Nabeel Asim, Koichi Kise, Sebastian J. Vollmer

CoRR, 2024

X Hacking: The Threat of Misguided AutoML.

Rahul Sharma, Sergey Redyuk, Sumantrak Mukherjee, Andrea Sipka, Sebastian J. Vollmer, David Antony Selby

CoRR, 2024

Peculiarities of Counterfactual Point Process Generation.

Gerrit Großmann, Sumantrak Mukherjee, Sebastian J. Vollmer

Proceedings of the 1st ACM SIGSPATIAL International Workshop on Spatiotemporal Causal Analysis, 2024

Single-Valued Risk Estimation for Segmentation Including Data Uncertainty.

Alexander Günther, Sebastian J. Vollmer, Peter Liggesmeyer

Proceedings of the 8th International Conference on System Reliability and Safety, 2024

Confidence-Aware Fault Trees.

Alexander Günther, Sebastian J. Vollmer, Peter Liggesmeyer

Proceedings of the 19th International Conference on Availability, Reliability and Security, 2024

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 B. 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 B. 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

Faking feature importance: A cautionary tale on the use of differentially-private synthetic data.

Oscar Giles, Kasra Hosseini, Grigorios Mingas, Oliver Strickson, Louise Bowler, Camila Rangel Smith, Harrison Wilde, Jen Ning Lim, Bilal A. Mateen, Kasun Amarasinghe, Rayid Ghani, Alison J. Heppenstall, Nik Lomax, Nick Malleson, Martin T. O'Reilly, Sebastian J. Vollmer

CoRR, 2022

F-EBM: Energy Based Learning of Functional Data.

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