Estimating vector fields using sparse basis field expansions. - Stefan Haufe; Vadim V. Nikulin; Andreas Ziehe; Klaus-Robert Müller; Guido Nolte (NIPS, 2008)

Combining sparsity and rotational invariance in EEG/MEG source reconstruction. - Stefan Haufe; Vadim V. Nikulin; Andreas Ziehe; Klaus-Robert Müller; Guido Nolte (NeuroImage, 2008)

Now You'll Feel It, Now You Won't: EEG Rhythms Predict the Effectiveness of Perceptual Masking. - Ruth Schubert; Stefan Haufe; Felix Blankenburg; Arno Villringer; Gabriel Curio (J. Cogn. Neurosci., 2009)

Sparse Causal Discovery in Multivariate Time Series. - Stefan Haufe; Klaus-Robert Müller; Guido Nolte; Nicole Krämer 002 (NIPS Causality: Objectives and Assessment, 2010)

Open Database of Epileptic EEG with MRI and Postoperational Assessment of Foci - a Real World Verification for the EEG Inverse Solutions. - Piotr Zwolinski; Marcin Roszkowski 002; Jaroslaw Zygierewicz; Stefan Haufe; Guido Nolte; Piotr J. Durka (Neuroinformatics, 2010)

Modeling Sparse Connectivity Between Underlying Brain Sources for EEG/MEG. - Stefan Haufe; Ryota Tomioka; Guido Nolte; Klaus-Robert Müller; Motoaki Kawanabe (IEEE Trans. Biomed. Eng., 2010)

Pitfalls in EEG-Based Brain Effective Connectivity Analysis. - Stefan Haufe; Vadim V. Nikulin; Guido Nolte; Klaus-Robert Müller (MLINI, 2011)

Single-trial analysis and classification of ERP components - A tutorial. - Benjamin Blankertz; Steven Lemm; Matthias Sebastian Treder; Stefan Haufe; Klaus-Robert Müller (NeuroImage, 2011)

Large-scale EEG/MEG source localization with spatial flexibility. - Stefan Haufe; Ryota Tomioka; Thorsten Dickhaus; Claudia Sannelli; Benjamin Blankertz; Guido Nolte; Klaus-Robert Müller (NeuroImage, 2011)

Alleviating the Influence of Weak Data Asymmetries on Granger-Causal Analyses. - Stefan Haufe; Vadim V. Nikulin; Guido Nolte (LVA/ICA, 2012)

Detection of multi-class emergency situations during simulated driving from ERP. - Il-Hwa Kim; Jeong-Woo Kim; Stefan Haufe; Seong-Whan Lee (BCI, 2013)

Decoding cognitive brain states. - Anne K. Porbadnigk; Matthias Sebastian Treder; Siamac Fazli; Michael Tangermann; Carmen Vidaurre; Stefan Haufe; Gabriel Curio; Benjamin Blankertz; Klaus-Robert Müller (BCI, 2013)

A critical assessment of connectivity measures for EEG data: A simulation study. - Stefan Haufe; Vadim V. Nikulin; Klaus-Robert Müller; Guido Nolte (NeuroImage, 2013)

Brain-computer interface for smart vehicle: Detection of braking intention during simulated driving. - Jeong-Woo Kim; Il-Hwa Kim; Stefan Haufe; Seong-Whan Lee (BCI, 2014)

Optimizing spatial filters for the extraction of envelope-coupled neural oscillations. - Sven Dähne; Vadim V. Nikulin; David Ramírez 001; Peter J. Schreier; Klaus-Robert Müller; Stefan Haufe (PRNI, 2014)

Parameter interpretation, regularization and source localization in multivariate linear models. - Stefan Haufe; Frank C. Meinecke; Kai Görgen; Sven Dähne; John-Dylan Haynes; Benjamin Blankertz; Felix Bießmann (PRNI, 2014)

The effect of linear mixing in the EEG on Hurst exponent estimation. - Duncan A. J. Blythe; Stefan Haufe; Klaus-Robert Müller; Vadim V. Nikulin (NeuroImage, 2014)

SPoC: A novel framework for relating the amplitude of neuronal oscillations to behaviorally relevant parameters. - Sven Dähne; Frank C. Meinecke; Stefan Haufe; Johannes Höhne; Michael Tangermann; Klaus-Robert Müller; Vadim V. Nikulin (NeuroImage, 2014)

Finding brain oscillations with power dependencies in neuroimaging data. - Sven Dähne; Vadim V. Nikulin; David Ramírez 001; Peter J. Schreier; Klaus-Robert Müller; Stefan Haufe (NeuroImage, 2014)

Dimensionality reduction for the analysis of brain oscillations. - Stefan Haufe; Sven Dähne; Vadim V. Nikulin (NeuroImage, 2014)

On the interpretation of weight vectors of linear models in multivariate neuroimaging. - Stefan Haufe; Frank C. Meinecke; Kai Görgen; Sven Dähne; John-Dylan Haynes; Benjamin Blankertz; Felix Bießmann (NeuroImage, 2014)

An extendable simulation framework for benchmarking EEG-based brain connectivity estimation methodologies. - Stefan Haufe (EMBC, 2015)

Solving the EEG inverse problem based on space-time-frequency structured sparsity constraints. - Sebastián Castaño-Candamil; Johannes Höhne; Juan David Martínez-Vargas; Xing-Wei An; Germán Castellanos-Domínguez; Stefan Haufe (NeuroImage, 2015)

Identifying Granger causal relationships between neural power dynamics and variables of interest. - Irene Winkler; Stefan Haufe; Anne K. Porbadnigk; Klaus-Robert Müller; Sven Dähne (NeuroImage, 2015)

Multivariate Machine Learning Methods for Fusing Multimodal Functional Neuroimaging Data. - Sven Dähne; Felix Bießmann; Wojciech Samek; Stefan Haufe; Dominique Goltz; Christopher Gundlach; Arno Villringer; Siamac Fazli; Klaus-Robert Müller (Proc. IEEE, 2015)

The New York Head - A precise standardized volume conductor model for EEG source localization and tES targeting. - Yu Huang 014; Lucas C. Parra; Stefan Haufe (NeuroImage, 2016)

Validity of Time Reversal for Testing Granger Causality. - Irene Winkler; Danny Panknin; Daniel Bartz; Klaus-Robert Müller; Stefan Haufe (IEEE Trans. Signal Process., 2016)

Consistency of EEG source localization and connectivity estimates. - Keyvan Mahjoory; Vadim V. Nikulin; Loïc Botrel; Klaus Linkenkaer-Hansen; Marco Fato; Stefan Haufe (NeuroImage, 2017)

Improving EEG Source Localization Through Spatio-Temporal Sparse Bayesian Learning. - Ali Hashemi 002; Stefan Haufe (EUSIPCO, 2018)

Correlated Components Analysis - Extracting Reliable Dimensions in Multivariate Data. - Lucas C. Parra; Stefan Haufe; Jacek P. Dmochowski (CoRR, 2018)

Elucidating relations between fMRI, ECoG, and EEG through a common natural stimulus. - Stefan Haufe; Paul DeGuzman; Simon Henin; Michael Arcaro; Christopher J. Honey; Uri Hasson; Lucas C. Parra (NeuroImage, 2018)

A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI. - Tao Tu 001; John W. Paisley; Stefan Haufe; Paul Sajda (NeurIPS, 2019)

Enhancing sensorimotor BCI performance with assistive afferent activity: An online evaluation. - Carmen Vidaurre; Ander Ramos-Murguialday; Stefan Haufe; Marisol Gómez; Klaus-Robert Müller; Vadim V. Nikulin (NeuroImage, 2019)

Functional connectivity of EEG is subject-specific, associated with phenotype, and different from fMRI. - Maximilian Nentwich; Lei Ai; Jens Madsen; Qawi K. Telesford; Stefan Haufe; Michael P. Milham; Lucas C. Parra (NeuroImage, 2020)

Efficient hierarchical Bayesian inference for spatio-temporal regression models in neuroimaging. - Ali Hashemi 002; Yijing Gao; Chang Cai; Sanjay Ghosh; Klaus-Robert Müller; Srikantan S. Nagarajan; Stefan Haufe (NeurIPS, 2021)

Evaluating saliency methods on artificial data with different background types. - Céline Budding; Fabian Eitel; Kerstin Ritter; Stefan Haufe (CoRR, 2021)

Machine Learning for Health: Algorithm Auditing & Quality Control. - Luis Oala; Andrew G. Murchison; Pradeep Balachandran; Shruti Choudhary; Jana Fehr; Alixandro Werneck Leite; Peter G. Goldschmidt; Christian Johner; Elora D. M. Schörverth; Rose Nakasi; Martin Meyer; Federico Cabitza; et al. (J. Medical Syst., 2021)

Robust estimation of noise for electromagnetic brain imaging with the champagne algorithm. - Chang Cai; Ali Hashemi 002; Mithun Diwakar; Stefan Haufe; Kensuke Sekihara; Srikantan S. Nagarajan (NeuroImage, 2021)

Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework. - Ali Hashemi 002; Chang Cai; Gitta Kutyniok; Klaus-Robert Müller; Srikantan S. Nagarajan; Stefan Haufe (NeuroImage, 2021)

Scrutinizing XAI using linear ground-truth data with suppressor variables. - Rick Wilming; Céline Budding; Klaus-Robert Müller; Stefan Haufe (Mach. Learn., 2022)

Empirical Bayesian localization of event-related time-frequency neural activity dynamics. - Chang Cai; Leighton B. N. Hinkley; Yijing Gao; Ali Hashemi 002; Stefan Haufe; Kensuke Sekihara; Srikantan S. Nagarajan (NeuroImage, 2022)

A benchmark for prediction of psychiatric multimorbidity from resting EEG data in a large pediatric sample. - Nicolas Langer; Martyna Beata Plomecka; Marius Tröndle; Anuja Negi; Tzvetan Popov; Michael P. Milham; Stefan Haufe (NeuroImage, 2022)

Theoretical Behavior of XAI Methods in the Presence of Suppressor Variables. - Rick Wilming; Leo Kieslich; Benedict Clark; Stefan Haufe (ICML, 2023)

Bayesian Inference for Brain Source Imaging with Joint Estimation of Structured Low-Rank Noise. - Sanjay Ghosh; Chang Cai; Yijing Gao; Ali Hashemi 002; Stefan Haufe; Kensuke Sekihara; Ashish Raj; Srikantan S. Nagarajan (ISBI, 2023)

Benchmark data to study the influence of pre-training on explanation performance in MR image classification. - Marta Oliveira; Rick Wilming; Benedict Clark; Céline Budding; Fabian Eitel; Kerstin Ritter; Stefan Haufe (CoRR, 2023)

XAI-TRIS: Non-linear benchmarks to quantify ML explanation performance. - Benedict Clark; Rick Wilming; Stefan Haufe (CoRR, 2023)

Alterations in rhythmic and non-rhythmic resting-state EEG activity and their link to cognition in older age. - Elena Cesnaite; Paul Steinfath; Mina Jamshidi Idaji; Tilman Stephani; Deniz Kumral; Stefan Haufe; Christian Sander; Tilman Hensch; Ulrich Hegerl; Steffi Riedel-Heller; Susanne Röhr; Matthias L. Schroeter; et al. (NeuroImage, 2023)

Bayesian Algorithms for Joint Estimation of Brain Activity and Noise in Electromagnetic Imaging. - Chang Cai; Huicong Kang; Ali Hashemi 002; Dan Chen 001; Mithun Diwakar; Stefan Haufe; Kensuke Sekihara; Wei Wu 022; Srikantan S. Nagarajan (IEEE Trans. Medical Imaging, 2023)

Identifying good practices for detecting inter-regional linear functional connectivity from EEG. - Franziska Pellegrini; Arnaud Delorme; Vadim V. Nikulin; Stefan Haufe (NeuroImage, 2023)

Bayesian Adaptive Beamformer for Robust Electromagnetic Brain Imaging of Correlated Sources in High Spatial Resolution. - Chang Cai; Yuanshun Long; Sanjay Ghosh; Ali Hashemi 002; Yijing Gao; Mithun Diwakar; Stefan Haufe; Kensuke Sekihara; Wei Wu 022; Srikantan S. Nagarajan (IEEE Trans. Medical Imaging, 2023)

EXACT: Towards a platform for empirically benchmarking Machine Learning model explanation methods. - Benedict Clark; Rick Wilming; Artur Dox; Paul Eschenbach; Sami Hached; Daniel Jin Wodke; Michias Taye Zewdie; Uladzislau Bruila; Marta Oliveira; Hjalmar Schulz; Luca Matteo Cornils; Danny Panknin; et al. (CoRR, 2024)

GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations. - Rick Wilming; Artur Dox; Hjalmar Schulz; Marta Oliveira; Benedict Clark; Stefan Haufe (CoRR, 2024)

Explainable AI needs formal notions of explanation correctness. - Stefan Haufe; Rick Wilming; Benedict Clark; Rustam Zhumagambetov; Danny Panknin; Ahcène Boubekki (CoRR, 2024)

Enhancing Brain Source Reconstruction through Physics-Informed 3D Neural Networks. - Marco Morik; Ali Hashemi 002; Klaus-Robert Müller; Stefan Haufe; Shinichi Nakajima (CoRR, 2024)

Benchmarking the influence of pre-training on explanation performance in MR image classification. - Marta Oliveira; Rick Wilming; Benedict Clark; Céline Budding; Fabian Eitel; Kerstin Ritter; Stefan Haufe (Frontiers Artif. Intell., 2024)

A scalable approach for critical care data extraction and analysis in an academic medical center. - Sebastian Daniel Boie; Falk Meyer-Eschenbach; Fabian Schreiber; Niklas Giesa; Jon Barrenetxea; Camille Guinemer; Stefan Haufe; Michael Krämer; Peter Brunecker; Fabian Prasser; Felix Balzer (Int. J. Medical Informatics, 2024)

Joint Learning of Full-Structure Noise in Hierarchical Bayesian Regression Models. - Ali Hashemi 002; Chang Cai; Yijing Gao; Sanjay Ghosh; Klaus-Robert Müller; Srikantan S. Nagarajan; Stefan Haufe (IEEE Trans. Medical Imaging, 2024)

XAI-TRIS: non-linear image benchmarks to quantify false positive post-hoc attribution of feature importance. - Benedict Clark; Rick Wilming; Stefan Haufe (Mach. Learn., 2024)

Minimizing False-Positive Attributions in Explanations of Non-Linear Models. - Anders Gjølbye Madsen; Stefan Haufe; Lars Kai Hansen (CoRR, 2025)