| 2023 | DSAA | Interpretable time series neural representation for classification purposes. | Etienne Le Naour, Ghislain Agoua, Nicolas Baskiotis, Vincent Guigue |
| 2022 | ICML | Generalizing to New Physical Systems via Context-Informed Dynamics Model. | Matthieu Kirchmeyer, Yuan Yin, Jrmie Don, Nicolas Baskiotis, Alain Rakotomamonjy, Patrick Gallinari |
| 2017 | ESANN | Anomaly detection and characterization in smart card logs using NMF and Tweets. | Emeric Tonnelier, Nicolas Baskiotis, Vincent Guigue, Patrick Gallinari |
| 2017 | ICONIP | Binary Stochastic Representations for Large Multi-class Classification. | Thomas Gerald, Nicolas Baskiotis, Ludovic Denoyer |
| 2016 | ESANN | Learning Embeddings for Completion and Prediction of Relationnal Multivariate Time-Series. | Ali Ziat, Gabriella Contardo, Nicolas Baskiotis, Ludovic Denoyer |
| 2015 | DSAA | Hierarchical label partitioning for large scale classification. | Raphal Puget, Nicolas Baskiotis |
| 2015 | ICML | Car-Traffic Forecasting: A Representation Learning Approach. | Ali Ziat, Gabriella Contardo, Nicolas Baskiotis, Ludovic Denoyer |
| 2014 | ICECCS | Exact and Efficient Temporal Steering of Software Behavioral Model Inference. | Sylvain Lamprier, Tewfik Ziadi, Nicolas Baskiotis, Lom-Messan Hillah |
| 2013 | ICECCS | CARE: A Platform for Reliable Comparison and Analysis of Reverse-Engineering Techniques. | Sylvain Lamprier, Nicolas Baskiotis, Tewfik Ziadi, Lom-Messan Hillah |
| 2007 | IJCAI | A Machine Learning Approach for Statistical Software Testing. | Nicolas Baskiotis, Michle Sebag, Marie-Claude Gaudel, Sandrine-Dominique Gouraud |
| 2007 | ILP | Structural Statistical Software Testing with Active Learning in a Graph. | Nicolas Baskiotis, Michle Sebag |
| 2004 | ICML | C4.5 competence map: a phase transition-inspired approach. | Nicolas Baskiotis, Michle Sebag |