Dimension-Independent MCMC Sampling for Inverse Problems with Non-Gaussian Priors. - Sebastian J. Vollmer (SIAM/ASA J. Uncertain. Quantification, 2015)

Measuring Sample Quality with Diffusions. - Jack Gorham; Andrew B. Duncan; Sebastian J. Vollmer; Lester W. Mackey (CoRR, 2016)

Consistency and Fluctuations For Stochastic Gradient Langevin Dynamics. - Yee Whye Teh; Alexandre H. Thiéry; Sebastian J. Vollmer (J. Mach. Learn. Res., 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)

Relativistic Monte Carlo. - Xiaoyu Lu; Valerio Perrone; Leonard Hasenclever; Yee Whye Teh; Sebastian J. Vollmer (AISTATS, 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)

Multilevel Monte Carlo for Reliability Theory. - Louis J. M. Aslett; Tigran Nagapetyan; Sebastian J. Vollmer (Reliab. Eng. Syst. Saf., 2017)

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; et al. (CoRR, 2018)

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; et al. (CoRR, 2019)

Debiasing classifiers: is reality at variance with expectation? - Ashrya Agrawal; Florian Pfisterer; Bernd Bischl; Jiahao Chen 001; Srijan Sood; Sameena Shah; Francois Buet-Golfouse; Bilal A. Mateen; Sebastian J. Vollmer (CoRR, 2020)

Flexible model composition in machine learning and its implementation in MLJ. - Anthony D. Blaom; Sebastian J. Vollmer (CoRR, 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)

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)

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)

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 (AISTATS, 2021)

Foundations of Bayesian Learning from Synthetic Data. - Harrison Wilde; Jack Jewson; Sebastian J. Vollmer; Chris C. Holmes (AISTATS, 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)

Evaluation of survival distribution predictions with discrimination measures. - Raphael Sonabend; Andreas Bender 001; Sebastian J. Vollmer (CoRR, 2021)

Mitigating statistical bias within differentially private synthetic data. - Sahra Ghalebikesabi; Harry Wilde; Jack Jewson; Arnaud Doucet; Sebastian J. Vollmer; Chris C. Holmes (UAI, 2022)

Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures. - Raphael Sonabend; Andreas Bender 001; Sebastian J. Vollmer (Bioinform., 2022)

F-EBM: Energy Based Learning of Functional Data. - Jen Ning Lim; Sebastian J. Vollmer; Lorenz Wolf; Andrew B. Duncan (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; et al. (CoRR, 2022)

Flexible Group Fairness Metrics for Survival Analysis. - Raphael Sonabend; Florian Pfisterer; Alan Mishler; Moritz Schauer; Lukas Burk; Sebastian J. Vollmer (CoRR, 2022)

Energy-Based Models for Functional Data using Path Measure Tilting. - Jen Ning Lim; Sebastian J. Vollmer; Lorenz Wolf; Andrew B. Duncan (AISTATS, 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 (NeurIPS, 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)

Fairness Audits and Debiasing Using pkg{mlr3fairness}. - Florian Pfisterer; Siyi Wei; Sebastian J. Vollmer; Michel Lang; Bernd Bischl (R J., 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., 2023)

Confidence-Aware Fault Trees. - Alexander Günther; Sebastian J. Vollmer; Peter Liggesmeyer (ARES, 2024)

Single-Valued Risk Estimation for Segmentation Including Data Uncertainty. - Alexander Günther; Sebastian J. Vollmer; Peter Liggesmeyer (ICSRS, 2024)

Peculiarities of Counterfactual Point Process Generation. - Gerrit Großmann; Sumantrak Mukherjee; Sebastian J. Vollmer (STCausal@SIGSPATIAL, 2024)

X Hacking: The Threat of Misguided AutoML. - Rahul Sharma; Sergey Redyuk; Sumantrak Mukherjee; Andrea Sipka; Sebastian J. Vollmer; David Antony Selby (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)

Act as a Honeytoken Generator! An Investigation into Honeytoken Generation with Large Language Models. - Daniel Reti; Norman Becker; Tillmann Angeli; Anasuya Chattopadhyay; Daniel Schneider 007; Sebastian J. Vollmer; Hans D. Schotten (CoRR, 2024)

icon: Fast Simulation of Epidemics on Coevolving Networks. - Gerrit Großmann; Sebastian J. Vollmer (CoRR, 2024)

Graph Agnostic Causal Bayesian Optimisation. - Sumantrak Mukherjee; Mengyan Zhang; Seth R. Flaxman; Sebastian J. Vollmer (CoRR, 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 001 (Frontiers Artif. Intell., 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; et al. (npj Digit. Medicine, 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; et al. (npj Digit. Medicine, 2024)

Rethinking Cancer Gene Identification Through Graph Anomaly Analysis. - Yilong Zang; Lingfei Ren; Yue Li 038; Zhikang Wang; David Antony Selby; Zheng Wang 007; Sebastian Josef Vollmer; Hongzhi Yin; Jiangning Song; Junhang Wu (AAAI, 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)

CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning. - Yousef Koka; David Antony Selby; Gerrit Großmann; Sebastian J. Vollmer (CoRR, 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, 2025)

AI-Driven Diabetic Retinopathy Diagnosis Enhancement through Image Processing and Salp Swarm Algorithm-Optimized Ensemble Network. - Saif Ur Rehman Khan 002; Muhammad Nabeel Asim; Sebastian J. Vollmer; Andreas Dengel 001 (CoRR, 2025)

When Counterfactual Reasoning Fails: Chaos and Real-World Complexity. - Yahya Aalaila; Gerrit Großmann; Sumantrak Mukherjee; Jonas Wahl; Sebastian J. Vollmer (CoRR, 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, 2025)

Robust & Precise Knowledge Distillation-based Novel Context-Aware Predictor for Disease Detection in Brain and Gastrointestinal. - Saif Ur Rehman Khan 002; Muhammad Nabeel Asim; Sebastian J. Vollmer; Andreas Dengel 001 (CoRR, 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, 2025)

FOLC-Net: A Federated-Optimized Lightweight Architecture for Enhanced MRI Disease Diagnosis across Axial, Coronal, and Sagittal Views. - Saif Ur Rehman Khan 002; Muhammad Nabeel Asim; Sebastian J. Vollmer; Andreas Dengel 001 (CoRR, 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, 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, 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, 2025)

Automated Visualization Makeovers with LLMs. - Siddharth Gangwar; David Antony Selby; Sebastian J. Vollmer (CoRR, 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, 2025)