Sebastian J. Vollmer

71 papers A* 1A 5B 1Journal 60Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Automated Diabetic Screening via Anterior Segment Ocular Imaging: A Deep Learning and Explainable AI Approach. CoRR Hasaan Maqsood, Saif Ur Rehman Khan, Sebastian J. Vollmer, Andreas Dengel, Muhammad Nabeel Asim
2026	J	`jnl`	GlobalWasteData: A Large-Scale, Integrated Dataset for Robust Waste Classification and Environmental Monitoring. CoRR Misbah Ijaz, Saif Ur Rehman Khan, Abd Ur Rehman, Tayyaba Asif, Sebastian J. Vollmer, Andreas Dengel, Muhammad Nabeel Asim
2026	J	`jnl`	KI-Adventskalender: An Informal Learning Intervention for Data & AI Literacy. CoRR Rahul Sharma, Lars Henrich, Larisa Ivanova, Arsalan Karimzadmotallebiazar, Annette Bieniusa, Leo van Waveren, Sebastian J. Vollmer
2026	J	`jnl`	StructDamage:A Large Scale Unified Crack and Surface Defect Dataset for Robust Structural Damage Detection. CoRR Misbah Ijaz, Saif Ur Rehman Khan, Abd Ur Rehman, Sebastian J. Vollmer, Andreas Dengel, Muhammad Nabeel Asim
2026	J	`jnl`	Temperature-driven robust disease detection in brain and gastrointestinal disorders via context-aware adaptive knowledge distillation. Biomed. Signal Process. Control. Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian J. Vollmer, Andreas Dengel
2025	J	`jnl`	AI-Driven Diabetic Retinopathy Diagnosis Enhancement through Image Processing and Salp Swarm Algorithm-Optimized Ensemble Network. CoRR Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian J. Vollmer, Andreas Dengel
2025	J	`jnl`	Automated Visualization Makeovers with LLMs. CoRR Siddharth Gangwar, David Antony Selby, Sebastian J. Vollmer
2025	J	`jnl`	Benchmarking World-Model Learning. CoRR Archana Warrier, Dat Nguyen, Michelangelo Naim, Moksh Jain, Yichao Liang, Karen Schroeder, Cambridge Yang, Joshua B. Tenenbaum, Sebastian J. Vollmer, Kevin Ellis, Zenna Tavares
2025	J	`jnl`	BioDisco: Multi-agent hypothesis generation with dual-mode evidence, iterative feedback and temporal evaluation. CoRR Yujing Ke, Kevin George, Kathan Pandya, David Blumenthal, Maximilian Sprang, Gerrit Großmann, Sebastian J. Vollmer, David Antony Selby
2025	J	`jnl`	CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning. CoRR Yousef Koka, David Antony Selby, Gerrit Großmann, Sebastian J. Vollmer
2025	J	`jnl`	Decomposing Visual Classification: Assessing Tree-Based Reasoning in VLMs. CoRR Sary Elmansoury, Islam Mesabah, Gerrit Großmann, Peter Neigel, Raj Bhalwankar, Daniel Kondermann, Sebastian J. Vollmer
2025	J	`jnl`	Dynamic Weight Adjustment for Knowledge Distillation: Leveraging Vision Transformer for High-Accuracy Lung Cancer Detection and Real-Time Deployment. CoRR Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian J. Vollmer, Andreas Dengel
2025	—	`conf`	Exploring the Alignment of Perceived and Measured Sleep Quality with Working Memory Using Consumer Wearables. AHs Peter Neigel, David Antony Selby, Shota Arai, Benjamin Tag, Niels van Berkel, Sebastian J. Vollmer, Andrew Vargo, Koichi Kise
2025	J	`jnl`	Exploring the Alignment of Perceived and Measured Sleep Quality with Working Memory using Consumer Wearables. CoRR Peter Neigel, David Antony Selby, Shota Arai, Benjamin Tag, Niels van Berkel, Sebastian J. Vollmer, Andrew Vargo, Koichi Kise
2025	J	`jnl`	FOLC-Net: A Federated-Optimized Lightweight Architecture for Enhanced MRI Disease Diagnosis across Axial, Coronal, and Sagittal Views. CoRR Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian J. Vollmer, Andreas Dengel
2025	J	`jnl`	Finding Common Ground: Using Large Language Models to Detect Agreement in Multi-Agent Decision Conferences. CoRR Selina Heller, Mohamed Ibrahim, David Antony Selby, Sebastian J. Vollmer
2025	J	`jnl`	FloraSyntropy-Net: Scalable Deep Learning with Novel FloraSyntropy Archive for Large-Scale Plant Disease Diagnosis. CoRR Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian J. Vollmer, Andreas Dengel
2025	J	`jnl`	Formally Exploring Time-Series Anomaly Detection Evaluation Metrics. CoRR Dennis Wagner, Arjun Nair, Billy Joe Franks, Justus Arweiler, Aparna Muraleedharan, Indra Jungjohann, Fabian Hartung, Mayank C. Ahuja, Andriy Balinskyy, Saurabh Varshneya, Nabeel Hussain Syed, Mayank Nagda, Philipp Liznerski, Steffen Reithermann, Maja Rudolph, Sebastian J. Vollmer, Ralf Schulz, Torsten Katz, Stephan Mandt, Michael Bortz, Heike Leitte, Daniel Neider, Jakob Burger, Fabian Jirasek, Hans Hasse, Sophie Fellenz, Marius Kloft
2025	J	`jnl`	How many patients could we save with LLM priors? CoRR Shota Arai, David Antony Selby, Andrew Vargo, Sebastian J. Vollmer
2025	J	`jnl`	IMAGIC-500: IMputation benchmark on A Generative Imaginary Country (500k samples). CoRR Siyi Sun, David Antony Selby, Yunchuan Huang, Sebastian J. Vollmer, Seth R. Flaxman, Anisoara Calinescu
2025	J	`jnl`	Neural Spatiotemporal Point Processes: Trends and Challenges. CoRR Sumantrak Mukherjee, Mouad Elhamdi, George Mohler, David Antony Selby, Yao Xie, Sebastian J. Vollmer, Gerrit Grossmann
2025	J	`jnl`	Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems. CoRR Jan Tauberschmidt, Sophie Fellenz, Sebastian J. Vollmer, Andrew B. Duncan
2025	J	`jnl`	Robust & Precise Knowledge Distillation-based Novel Context-Aware Predictor for Disease Detection in Brain and Gastrointestinal. CoRR Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian J. Vollmer, Andreas Dengel
2025	J	`jnl`	The Power of Stories: Narrative Priming Shapes How LLM Agents Collaborate and Compete. CoRR Gerrit Großmann, Larisa Ivanova, Sai Leela Poduru, Mohaddeseh Tabrizian, Islam Mesabah, David Antony Selby, Sebastian J. Vollmer
2025	—	`conf`	The Power of Stories: Narrative Priming in Networked Multi-Agent LLM Interactions. NETGCOOP Gerrit Großmann, Larisa Ivanova, Sai Leela Poduru, Mohaddeseh Tabrizian, Islam Mesabah, David A. Selby, Sebastian J. Vollmer
2025	J	`jnl`	Visible neural networks for multi-omics integration: a critical review. Frontiers Artif. Intell. David Antony Selby, Rashika Jakhmola, Maximilian Sprang, Gerrit Großmann, Hind Raki, Niloofar Maani, Daria Pavliuk, Jan Ewald, Sebastian J. Vollmer
2025	J	`jnl`	When Counterfactual Reasoning Fails: Chaos and Real-World Complexity. CoRR Yahya Aalaila, Gerrit Großmann, Sumantrak Mukherjee, Jonas Wahl, Sebastian J. Vollmer
2024	J	`jnl`	Act as a Honeytoken Generator! An Investigation into Honeytoken Generation with Large Language Models. CoRR Daniel Reti, Norman Becker, Tillmann Angeli, Anasuya Chattopadhyay, Daniel Schneider, Sebastian J. Vollmer, Hans D. Schotten
2024	B	`conf`	Confidence-Aware Fault Trees. ARES Alexander Günther, Sebastian J. Vollmer, Peter Liggesmeyer
2024	J	`jnl`	Development and assessment of a machine learning tool for predicting emergency admission in Scotland. npj Digit. Medicine 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
2024	J	`jnl`	Graph Agnostic Causal Bayesian Optimisation. CoRR Sumantrak Mukherjee, Mengyan Zhang, Seth R. Flaxman, Sebastian J. Vollmer
2024	—	`conf`	Peculiarities of Counterfactual Point Process Generation. STCausal@SIGSPATIAL Gerrit Großmann, Sumantrak Mukherjee, Sebastian J. Vollmer
2024	J	`jnl`	Publisher Correction: Development and assessment of a machine learning tool for predicting emergency admission in Scotland. npj Digit. Medicine 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
2024	J	`jnl`	Quantitative knowledge retrieval from large language models. CoRR David Antony Selby, Kai Spriestersbach, Yuichiro Iwashita, Dennis Bappert, Archana Warrier, Sumantrak Mukherjee, Muhammad Nabeel Asim, Koichi Kise, Sebastian J. Vollmer
2024	J	`jnl`	Rethinking Cancer Gene Identification through Graph Anomaly Analysis. CoRR Yilong Zang, Lingfei Ren, Yue Li, Zhikang Wang, David Antony Selby, Zheng Wang, Sebastian J. Vollmer, Hongzhi Yin, Jiangning Song, Junhang Wu
2024	—	`conf`	Single-Valued Risk Estimation for Segmentation Including Data Uncertainty. ICSRS Alexander Günther, Sebastian J. Vollmer, Peter Liggesmeyer
2024	J	`jnl`	Survival prediction landscape: an in-depth systematic literature review on activities, methods, tools, diseases, and databases. Frontiers Artif. Intell. Ahtisham Fazeel Abbasi, Muhammad Nabeel Asim, Sheraz Ahmed, Sebastian J. Vollmer, Andreas Dengel
2024	J	`jnl`	X Hacking: The Threat of Misguided AutoML. CoRR Rahul Sharma, Sergey Redyuk, Sumantrak Mukherjee, Andrea Sipka, Sebastian J. Vollmer, David Antony Selby
2024	J	`jnl`	icon: Fast Simulation of Epidemics on Coevolving Networks. CoRR Gerrit Großmann, Sebastian J. Vollmer
2023	J	`jnl`	Comparison of causal forest and regression-based approaches to evaluate treatment effect heterogeneity: an application for type 2 diabetes precision medicine. BMC Medical Informatics Decis. Mak. Ashwini Venkatasubramaniam, Bilal A. Mateen, Beverley M. Shields, Andrew T. Hattersley, Angus G. Jones, Sebastian J. Vollmer, John M. Dennis
2023	A*	`conf`	Energy Discrepancies: A Score-Independent Loss for Energy-Based Models. NeurIPS Tobias Schröder, Zijing Ou, Jen Lim, Yingzhen Li, Sebastian J. Vollmer, Andrew B. Duncan
2023	J	`jnl`	Energy Discrepancies: A Score-Independent Loss for Energy-Based Models. CoRR Tobias Schröder, Zijing Ou, Jen Ning Lim, Yingzhen Li, Sebastian J. Vollmer, Andrew B. Duncan
2023	A	`conf`	Energy-Based Models for Functional Data using Path Measure Tilting. AISTATS Jen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew B. Duncan
2023	J	`jnl`	Fairness Audits and Debiasing Using \pkg{mlr3fairness}. R J. Florian Pfisterer, Siyi Wei, Sebastian J. Vollmer, Michel Lang, Bernd Bischl
2022	J	`jnl`	Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures. Bioinform. Raphael Sonabend, Andreas Bender, Sebastian J. Vollmer
2022	J	`jnl`	F-EBM: Energy Based Learning of Functional Data. CoRR Jen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew B. Duncan
2022	J	`jnl`	Faking feature importance: A cautionary tale on the use of differentially-private synthetic data. CoRR 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
2022	J	`jnl`	Flexible Group Fairness Metrics for Survival Analysis. CoRR Raphael Sonabend, Florian Pfisterer, Alan Mishler, Moritz Schauer, Lukas Burk, Sebastian J. Vollmer
2022	A	`conf`	Mitigating statistical bias within differentially private synthetic data. UAI Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes
2021	J	`jnl`	Bias Mitigated Learning from Differentially Private Synthetic Data: A Cautionary Tale. CoRR Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes
2021	J	`jnl`	Evaluation of survival distribution predictions with discrimination measures. CoRR Raphael Sonabend, Andreas Bender, Sebastian J. Vollmer
2021	A	`conf`	Foundations of Bayesian Learning from Synthetic Data. AISTATS Harrison Wilde, Jack Jewson, Sebastian J. Vollmer, Chris C. Holmes
2021	A	`conf`	Model updating after interventions paradoxically introduces bias. AISTATS James Liley, Samuel R. Emerson, Bilal A. Mateen, Catalina A. Vallejos, Louis J. M. Aslett, Sebastian J. Vollmer
2020	J	`jnl`	Debiasing classifiers: is reality at variance with expectation? CoRR Ashrya Agrawal, Florian Pfisterer, Bernd Bischl, Jiahao Chen, Srijan Sood, Sameena Shah, Francois Buet-Golfouse, Bilal A. Mateen, Sebastian J. Vollmer
2020	J	`jnl`	Flexible model composition in machine learning and its implementation in MLJ. CoRR Anthony D. Blaom, Sebastian J. Vollmer
2020	J	`jnl`	Foundations of Bayesian Learning from Synthetic Data. CoRR Harrison Wilde, Jack Jewson, Sebastian J. Vollmer, Chris C. Holmes
2020	J	`jnl`	Improving the quality of machine learning in health applications and clinical research. Nat. Mach. Intell. Bilal A. Mateen, James Liley, Alastair K. Denniston, Chris C. Holmes, Sebastian J. Vollmer
2020	J	`jnl`	MLJ: A Julia package for composable Machine Learning. CoRR Anthony D. Blaom, Franz J. Király, Thibaut Liénart, Yiannis Simillides, Diego Arenas, Sebastian J. Vollmer
2020	J	`jnl`	MLJ: A Julia package for composable machine learning. J. Open Source Softw. Anthony D. Blaom, Franz J. Király, Thibaut Liénart, Yiannis Simillides, Diego Arenas, Sebastian J. Vollmer
2020	J	`jnl`	Model updating after interventions paradoxically introduces bias. CoRR James Liley, Samuel R. Emerson, Bilal A. Mateen, Catalina A. Vallejos, Louis J. M. Aslett, Sebastian J. Vollmer
2020	J	`jnl`	Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations. Stat. Comput. Michael B. Giles, Mateusz B. Majka, Lukasz Szpruch, Sebastian J. Vollmer, Konstantinos C. Zygalakis
2019	J	`jnl`	Design choices for productive, secure, data-intensive research at scale in the cloud. CoRR 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
2018	J	`jnl`	Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness. CoRR 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
2017	J	`jnl`	Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server. J. Mach. Learn. Res. Leonard Hasenclever, Stefan Webb, Thibaut Liénart, Sebastian J. Vollmer, Balaji Lakshminarayanan, Charles Blundell, Yee Whye Teh
2017	J	`jnl`	Multilevel Monte Carlo for Reliability Theory. Reliab. Eng. Syst. Saf. Louis J. M. Aslett, Tigran Nagapetyan, Sebastian J. Vollmer
2017	A	`conf`	Relativistic Monte Carlo. AISTATS Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever, Yee Whye Teh, Sebastian J. Vollmer
2016	J	`jnl`	Consistency and Fluctuations For Stochastic Gradient Langevin Dynamics. J. Mach. Learn. Res. Yee Whye Teh, Alexandre H. Thiéry, Sebastian J. Vollmer
2016	J	`jnl`	Exploration of the (Non-)Asymptotic Bias and Variance of Stochastic Gradient Langevin Dynamics. J. Mach. Learn. Res. Sebastian J. Vollmer, Konstantinos C. Zygalakis, Yee Whye Teh
2016	J	`jnl`	Measuring Sample Quality with Diffusions. CoRR Jack Gorham, Andrew B. Duncan, Sebastian J. Vollmer, Lester W. Mackey
2015	J	`jnl`	Dimension-Independent MCMC Sampling for Inverse Problems with Non-Gaussian Priors. SIAM/ASA J. Uncertain. Quantification Sebastian J. Vollmer
2015	J	`jnl`	Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server. CoRR Yee Whye Teh, Leonard Hasenclever, Thibaut Liénart, Sebastian J. Vollmer, Stefan Webb, Balaji Lakshminarayanan, Charles Blundell