Publications
Find here some of the latest EPFL research papers and conference papers on the various fields related to intelligent systems.
Please note that (1) these lists show the five latest publications in each category, and that (2) neither the categories nor the lists are exhaustive. For more articles, please visit the portal EPFL InfoScience or contact our team at [email protected]
Artificial Intelligence
Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design
V. Swamy; S. Du; M. Marras; T. Käser
2023-03-13. LAK 2023: The 13th International Learning Analytics and Knowledge Conference, Arlington, Texas, USA, March 13-17, 2023. DOI : 10.1145/3576050.3576147. End-to-end kernel learning via generative random Fourier features
K. Fang; F. Liu; X. Huang; J. Yang
Pattern Recognition. 2023-02-01. Vol. 134, p. 109057. DOI : 10.1016/j.patcog.2022.109057.
Computer Vision
Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors
T. Riedlinger; M. Rottmann; M. Schubert; H. Gottschalk
2023. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, USA, January 3-7, 2023. Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification
M. Rottmann; M. Reese
2023. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, USA, January 3-7, 2023. Composite Relationship Fields with Transformers for Scene Graph Generation
G. Adaimi; D. Mizrahi; A. Alahi
2023. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2023), Waikoloa, Hawaii, United States, January 3-7, 2023. Multi-view Tracking Using Weakly Supervised Human Motion Prediction
M. Engilberge; W. Liu; P. Fua
2023. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2023), Waikoloa, Hawaii, USA, January 3-7, 2023.
Digital Twin
A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives
A. Thelen; X. Zhang; O. Fink; Y. Lu; S. Ghosh et al.
Structural And Multidisciplinary Optimization. 2023-01-01. Vol. 66, num. 1, p. 1. DOI : 10.1007/s00158-022-03410-x. A comprehensive review of digital twin – part 1: modeling and twinning enabling technologies
A. Thelen; X. Zhang; O. Fink; Y. Lu; S. Ghosh et al.
Structural And Multidisciplinary Optimization. 2022-12-01. Vol. 65, num. 12, p. 354. DOI : 10.1007/s00158-022-03425-4. A semantic-driven tradespace framework to accelerate aircraft manufacturing system design
X. Zheng; X. Hu; R. Arista; J. Lu; J. Sorvari et al.
Journal Of Intelligent Manufacturing. 2022-10-25. DOI : 10.1007/s10845-022-02043-7. Ontology-centric industrial requirements validation for aircraft assembly system design
X. Hu; R. Arista; J. Lentes; J. Lu; X. Zheng et al.
2022-10-01. 10th IFAC Triennial Conference on Manufacturing Modelling, Management and Control (MIM), Nantes, FRANCE, Jun 22-24, 2022. p. 3016-3021. DOI : 10.1016/j.ifacol.2022.10.191.
Intelligent Systems

Electro-Adhesive Tubular Clutch for Variable-Stiffness Robots
Y. Sun; K. M. Digumarti; H. V. Phan; O. Aloui; D. Floreano
2022-12-26. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan, October 23-27, 2022. p. 9628-9634. DOI : 10.1109/IROS47612.2022.9982098. Identifying and Classifying Urban Data Sources for Machine Learning-Based Sustainable Urban Planning and Decision Support Systems Development
S. C. K. Tekouabou; J. Chenal; R. Azmi; H. Toulni; E. B. Diop et al.
Data. 2022-12-01. Vol. 7, num. 12, p. 170. DOI : 10.3390/data7120170. Improving Students Argumentation Learning with Adaptive Self-Evaluation Nudging
T. Wambsganss; A. Janson; T. Käser; J. M. Leimeister
Proceedings of the ACM on Human-Computer Interaction. 2022-11-11. Vol. 6, num. CSCW2, p. 1-31. DOI : 10.1145/3555633. Optimizing Two-Truck Platooning With Deadlines
W. Xu; T. Cui; M. Chen
Ieee Transactions On Intelligent Transportation Systems. 2022-11-09. DOI : 10.1109/TTS.2022.3213549.
Machine Learning
Predicting and optimizing syngas production from fluidized bed biomass gasifiers: A machine learning approach
J. Y. Kim; D. Kim; Z. Li; C. Dariva; Y. Cao et al.
Energy. 2023-01-15. Vol. 263, p. 125900. DOI : 10.1016/j.energy.2022.125900. A low-temperature prismatic slip instability in Mg understood using machine learning potentials
X. Liu; M. R. Niazi; T. Liu; B. Yin; W. A. Curtin
Acta Materialia. 2023-01-15. Vol. 243, p. 118490. DOI : 10.1016/j.actamat.2022.118490. A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives
A. Thelen; X. Zhang; O. Fink; Y. Lu; S. Ghosh et al.
Structural And Multidisciplinary Optimization. 2023-01-01. Vol. 66, num. 1, p. 1. DOI : 10.1007/s00158-022-03410-x.
Robotics
Dissecting the photoacidity of spiropyran/merocyanine molecular switches in water.
C. Berton / K. Severin; C. Pezzato (Dir.)
Lausanne, EPFL, 2023. The effects of kinematics, flexibility, and planform on the vortex formation and aerodynamic performance of flapping wing flight
A. Gehrke / K. A. J. Mulleners (Dir.)
Lausanne, EPFL, 2023. 
Electro-Adhesive Tubular Clutch for Variable-Stiffness Robots
Y. Sun; K. M. Digumarti; H. V. Phan; O. Aloui; D. Floreano
2022-12-26. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan, October 23-27, 2022. p. 9628-9634. DOI : 10.1109/IROS47612.2022.9982098. Deconstructing body axis morphogenesis in zebrafish embryos using robot-assisted tissue micromanipulation
E. Özelçi; E. Mailand; M. Rüegg; A. C. Oates; S. Sakar
Nature Communications. 2022-12-24. Vol. 13, p. 7934. DOI : 10.1038/s41467-022-35632-4.