Mathieu Sinn
Mathieu Sinn
IBM Research Staff Member
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Cited by
Cited by
Adversarial Robustness Toolbox v1. 0.0
MI Nicolae, M Sinn, MN Tran, B Buesser, A Rawat, M Wistuba, ...
arXiv preprint arXiv:1807.01069, 2018
Ordinal analysis of time series
K Keller, M Sinn
Physica A: Statistical Mechanics and its Applications 356 (1), 114-120, 2005
Ibm federated learning: an enterprise framework white paper v0. 1
H Ludwig, N Baracaldo, G Thomas, Y Zhou, A Anwar, S Rajamoni, Y Ong, ...
arXiv preprint arXiv:2007.10987, 2020
One button machine for automating feature engineering in relational databases
HT Lam, JM Thiebaut, M Sinn, B Chen, T Mai, O Alkan
arXiv preprint arXiv:1706.00327, 2017
Predicting arrival times of buses using real-time GPS measurements
M Sinn, JW Yoon, F Calabrese, E Bouillet
2012 15th International IEEE Conference on Intelligent Transportation …, 2012
Defining the quantitative limits of intravital two-photon lymphocyte tracking
J Textor, A Peixoto, SE Henrickson, M Sinn, UH Von Andrian, ...
Proceedings of the National Academy of Sciences 108 (30), 12401-12406, 2011
Improved electricity load forecasting via kernel spectral clustering of smart meters
C Alzate, M Sinn
2013 IEEE 13th International Conference on Data Mining, 943-948, 2013
Time series from the ordinal viewpoint
K Keller, M Sinn, J Emonds
Stochastics and Dynamics 7 (02), 247-272, 2007
Uncertainty in urban mobility: Predicting waiting times for shared bicycles and parking lots
B Chen, F Pinelli, M Sinn, A Botea, F Calabrese
16th International IEEE Conference on Intelligent Transportation Systems …, 2013
Estimation of arrival times at transit stops
EP Bouillet, F Calabrese, F Pinelli, M Sinn, JW Yoon
US Patent 9,183,741, 2015
Kolmogorov–Sinai entropy from the ordinal viewpoint
K Keller, M Sinn
Physica D: Nonlinear Phenomena 239 (12), 997-1000, 2010
Adaptive learning of smoothing functions: Application to electricity load forecasting
A Ba, M Sinn, Y Goude, P Pompey
Advances in neural information processing systems 25, 2012
Estimation of ordinal pattern probabilities in Gaussian processes with stationary increments
M Sinn, K Keller
Computational Statistics & Data Analysis 55 (4), 1781-1790, 2011
Fat: Federated adversarial training
G Zizzo, A Rawat, M Sinn, B Buesser
arXiv preprint arXiv:2012.01791, 2020
Ordinal analysis of EEG time series
K Keller, H Lauffer, M Sinn
Chaos and Complexity Letters 2, 247-258, 2007
Detecting change-points in time series by maximum mean discrepancy of ordinal pattern distributions
M Sinn, A Ghodsi, K Keller
arXiv preprint arXiv:1210.4903, 2012
Automated image data preprocessing with deep reinforcement learning
TN Minh, M Sinn, HT Lam, M Wistuba
arXiv preprint arXiv:1806.05886, 2018
Forecasting uncertainty in electricity demand
TK Wijaya, M Sinn, B Chen
Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
A standardized approach to the Kolmogorov–Sinai entropy
K Keller, M Sinn
Nonlinearity 22 (10), 2417, 2009
Segmentation and classification of time series using ordinal pattern distributions
M Sinn, K Keller, B Chen
The European Physical Journal Special Topics 222 (2), 587-598, 2013
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