Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker. - Farheen Omar; Mathieu Sinn; Jakub Truszkowski; Pascal Poupart; James Yungjen Tung; Allen Caine (UAI, 2010)

Ambulatory Assessment of Lifestyle Factors for Alzheimer's Disease and Related Dementias. - James Yungjen Tung; Jonathan F. L. Semple; Wei X. Woo; Wei-Shou Hsu; Mathieu Sinn; Eric A. Roy; Pascal Poupart (AAAI Spring Symposium: Computational Physiology, 2011)

Smart walkers!: enhancing the mobility of the elderly. - Mathieu Sinn; Pascal Poupart (AAMAS, 2011)

Error Bounds for Online Predictions of Linear-Chain Conditional Random Fields: Application to Activity Recognition for Users of Rolling Walkers. - Mathieu Sinn; Pascal Poupart (ICMLA (2), 2011)

Estimation of ordinal pattern probabilities in Gaussian processes with stationary increments. - Mathieu Sinn; Karsten Keller (Comput. Stat. Data Anal., 2011)

Asymptotic Theory for Linear-Chain Conditional Random Fields. - Mathieu Sinn; Pascal Poupart (AISTATS, 2011)

Predicting arrival times of buses using real-time GPS measurements. - Mathieu Sinn; Ji Won Yoon; Francesco Calabrese; Eric Bouillet (ITSC, 2012)

Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting. - Amadou Ba; Mathieu Sinn; Yannig Goude; Pascal Pompey (NIPS, 2012)

Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions. - Mathieu Sinn; Bei Chen (NIPS, 2012)

Detecting Change-Points in Time Series by Maximum Mean Discrepancy of Ordinal Pattern Distributions. - Mathieu Sinn; Ali Ghodsi 001; Karsten Keller (UAI, 2012)

Central Limit Theorems for Conditional Markov Chains. - Mathieu Sinn; Bei Chen (AISTATS, 2013)

The effect of feedback in the assignment problem in shared bicycle systems. - Arieh Schlote; Bei Chen; Mathieu Sinn; Robert Shorten (ICCVE, 2013)

Improved Electricity Load Forecasting via Kernel Spectral Clustering of Smart Meters. - Carlos Alzate; Mathieu Sinn (ICDM, 2013)

Integrated state estimation and load modelling for distribution grids with ampere measurements. - Francesco Fusco; Mathieu Sinn (ISGT Europe, 2013)

Uncertainty in urban mobility: Predicting waiting times for shared bicycles and parking lots. - Bei Chen; Fabio Pinelli; Mathieu Sinn; Adi Botea; Francesco Calabrese (ITSC, 2013)

Analytical results on the Beauchemin model of lymphocyte migration. - Johannes Textor; Mathieu Sinn; Rob J. De Boer (BMC Bioinform., 2013)

Energy demand forecasting: industry practices and challenges. - Mathieu Sinn (e-Energy, 2014)

Statistical Anomaly Detection in Mean and Variation of Energy Consumption. - Bei Chen; Mathieu Sinn; Joern Ploennigs; Anika Schumann (ICPR, 2014)

Forecasting Uncertainty in Electricity Demand. - Tri Kurniawan Wijaya; Mathieu Sinn; Bei Chen (AAAI Workshop: Computational Sustainability, 2015)

Multi-task additive models with shared transfer functions based on dictionary learning. - Alhussein Fawzi; Mathieu Sinn; Pascal Frossard (CoRR, 2015)

Data Management System for Energy Analytics and its Application to Forecasting. - Francesco Fusco; Ulrike Fischer; Vincent P. A. Lonij; Pascal Pompey; Jean-Baptiste Fiot; Bei Chen; Yiannis Gkoufas; Mathieu Sinn (EDBT/ICDT Workshops, 2016)

Enabling coupled models to predict the business impact of weather on electric utilities. - Lloyd A. Treinish; James P. Cipriani; Anthony Praino; Amith Singhee; H. Wang; Mathieu Sinn; Vincent P. A. Lonij; Jean-Baptiste Fiot; B. Chen (IBM J. Res. Dev., 2016)

Managing uncertainty in electricity generation and demand forecasting. - Kevin Warren; Ron F. Ambrosio; Bei Chen; Yuhui Fu 001; Soumyadip Ghosh; Dzung T. Phan; Mathieu Sinn; Chunhua Tian; Chandu Visweswariah (IBM J. Res. Dev., 2016)

Structured Dimensionality Reduction for Additive Model Regression. - Alhussein Fawzi; Jean-Baptiste Fiot; Bei Chen; Mathieu Sinn; Pascal Frossard (IEEE Trans. Knowl. Data Eng., 2016)

Cross-correlations of zero crossings in jointly Gaussian and stationary processes with zero means. - Magnus Mossberg; Mathieu Sinn (ICASSP, 2017)

One button machine for automating feature engineering in relational databases. - Hoang Thanh Lam; Johann-Michael Thiebaut; Mathieu Sinn; Bei Chen; Tiep Mai; Oznur Alkan (CoRR, 2017)

Multitask Additive Models With Shared Transfer Functions Based on Dictionary Learning. - Alhussein Fawzi; Mathieu Sinn; Pascal Frossard (IEEE Trans. Signal Process., 2017)

Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training. - Mathieu Sinn; Ambrish Rawat (AISTATS, 2018)

Castor: Contextual IoT Time Series Data and Model Management at Scale. - Bei Chen; Bradley Eck; Francesco Fusco; Robert Gormally; Mark Purcell; Mathieu Sinn; Seshu Tirupathi (ICDM Workshops, 2018)

Learning Features For Relational Data. - Hoang Thanh Lam; Tran Ngoc Minh; Mathieu Sinn; Beat Buesser; Martin Wistuba (CoRR, 2018)

Learning Correlation Space for Time Series. - Han Qiu 005; Hoang Thanh Lam; Francesco Fusco; Mathieu Sinn (CoRR, 2018)

Automated Image Data Preprocessing with Deep Reinforcement Learning. - Tran Ngoc Minh; Mathieu Sinn; Hoang Thanh Lam; Martin Wistuba (CoRR, 2018)

Adversarial Robustness Toolbox v0.2.2. - Maria-Irina Nicolae; Mathieu Sinn; Tran Ngoc Minh; Ambrish Rawat; Martin Wistuba; Valentina Zantedeschi; Ian M. Molloy; Benjamin Edwards (CoRR, 2018)

Exploring the Hyperparameter Landscape of Adversarial Robustness. - Evelyn Duesterwald; Anupama Murthi; Ganesh Venkataraman; Mathieu Sinn; Deepak Vijaykeerthy (CoRR, 2019)

IBM Federated Learning: an Enterprise Framework White Paper V0.1. - Heiko Ludwig; Nathalie Baracaldo; Gegi Thomas; Yi Zhou 015; Ali Anwar 001; Shashank Rajamoni; Yuya Jeremy Ong; Jayaram Radhakrishnan; Ashish Verma 001; Mathieu Sinn; Mark Purcell; Ambrish Rawat; et al. (CoRR, 2020)

FAT: Federated Adversarial Training. - Giulio Zizzo; Ambrish Rawat; Mathieu Sinn; Beat Buesser (CoRR, 2020)

Accountable Federated Machine Learning in Government: Engineering and Management Insights. - Dian Balta; Mahdi Sellami; Peter Kuhn; Ulrich Schöpp; Matthias Buchinger; Nathalie Baracaldo; Ali Anwar 001; Heiko Ludwig; Mathieu Sinn; Mark Purcell; Bashar Altakrouri (ePart, 2021)

The Devil is in the GAN: Defending Deep Generative Models Against Backdoor Attacks. - Ambrish Rawat; Killian Levacher; Mathieu Sinn (CoRR, 2021)

Automated Robustness with Adversarial Training as a Post-Processing Step. - Ambrish Rawat; Mathieu Sinn; Beat Buesser (CoRR, 2021)

Certified Federated Adversarial Training. - Giulio Zizzo; Ambrish Rawat; Mathieu Sinn; Sergio Maffeis; Chris Hankin (CoRR, 2021)

DLPFS: The Data Leakage Prevention FileSystem. - Stefano Braghin; Marco Simioni; Mathieu Sinn (ACNS Workshops, 2022)

The Devil Is in the GAN: Backdoor Attacks and Defenses in Deep Generative Models. - Ambrish Rawat; Killian Levacher; Mathieu Sinn (ESORICS (3), 2022)

Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach. - Nathalie Baracaldo; Ali Anwar 001; Mark Purcell; Ambrish Rawat; Mathieu Sinn; Bashar Altakrouri; Dian Balta; Mahdi Sellami; Peter Kuhn; Ulrich Schöpp; Matthias Buchinger (CoRR, 2022)