Tammo Rukat
Tammo Rukat
Verified email at dtc.ox.ac.uk - Homepage
TitleCited byYear
Chain-length dependent growth dynamics of n-alkanes on silica investigated by energy-dispersive x-ray reflectivity in situ and in real-time
C Weber, C Frank, S Bommel, T Rukat, W Leitenberger, P Schäfer, ...
The Journal of chemical physics 136 (20), 204709, 2012
Bayesian Boolean matrix factorisation
T Rukat, CC Holmes, MK Titsias, C Yau
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
Resting state brain networks from EEG: Hidden Markov states vs. classical microstates
T Rukat, A Baker, A Quinn, M Woolrich
arXiv preprint arXiv:1606.02344, 2016
Dynamic contrast‐enhanced MRI in mice: An investigation of model parameter uncertainties
T Rukat, S Walker‐Samuel, SA Reinsberg
Magnetic resonance in medicine 73 (5), 1979-1987, 2015
Probabilistic boolean tensor decomposition
T Rukat, C Holmes, C Yau
International conference on machine learning, 4410-4419, 2018
Ten simple rules for surviving an interdisciplinary PhD
S Demharter, N Pearce, K Beattie, I Frost, J Leem, A Martin, ...
PLoS computational biology 13 (5), e1005512, 2017
An interpretable latent variable model for attribute applicability in the amazon catalogue
T Rukat, D Lange, C Archambeau
arXiv preprint arXiv:1712.00126, 2017
Differential Data Quality Verification on Partitioned Data
S Schelter, S Grafberger, P Schmidt, T Rukat, M Kiessling, A Taptunov, ...
2019 IEEE 35th International Conference on Data Engineering (ICDE), 1940-1945, 2019
Bayesian Nonparametric Boolean Factor Models
T Rukat, C Yau
arXiv preprint arXiv:1907.00063, 2019
Unit Testing Data with Deequ
S Schelter, F Biessmann, D Lange, T Rukat, P Schmidt, S Seufert, ...
Proceedings of the 2019 International Conference on Management of Data, 1993 …, 2019
Learning to Validate the Predictions of Black Box Machine Learning Models on Unseen Data
S Redyuk, S Schelter, T Rukat, V Markl, F Biessmann
TensOrMachine: Probabilistic Boolean Tensor Decomposition
T Rukat, CC Holmes, C Yau
arXiv preprint arXiv:1805.04582, 2018
Logical factorisation machines: probabilistic boolean factor models for binary data
T Rukat
University of Oxford, 2018
Deequ-Data Quality Validation for Machine Learning Pipelines
S Schelter, S Grafberger, P Schmidt, T Rukat, M Kiessling, A Taptunov, ...
Machine Learning Systems Workshop, NeurIPS, 2018
Information Criteria weighted Parameter Estimates in DCE-MRI
T Rukat, SA Reinsberg
AIF Induced Limits of Parameter Uncertainty in Pharmakokinetic Models of Pre-Clinical DCE-MRI
T Rukat, S Walker-Samuel, SA Reinsberg
Fully Bayesian Multi-Model Inference for Parameter Estimation in DCE-MRI
T Rukat, SA Reinsberg
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Articles 1–17