Vlad Nitu, ANR Young Researchers (JCJC) laureate
The JCJC financing instrument allows project leaders to independently research on a specific theme. Its purpose is to support young researchers in the development of their research program and to promote responsibility and the capacity for scientific innovation. Vlad Nitu, a CNRS research fellow in the DRIM team, is the new JCJC laureate.
L'institut INS2I du CNRS lance la bande dessinée "Les décodeuses du numérique"
L'Institut des sciences de l'information et de leurs interactions (INS2I) du CNRS a souhaité mettre en avant la diversité des recherches en sciences du numérique et contribuer à briser les stéréotypes qui dissuadent les femmes de s’engager dans cette voie.
AfterLab : Post PhD, where do I go from here?
What to do with a PhD in computer science? A round-table meeting is organised at LIRIS on Tuesday, June 29 for students nearing the end of their thesis (and all those who wish to have useful information on the post-Doc period). This meeting is an opportunity to listen to three PhDs in computer science (whose PhD took place at LIRIS) reflecting the diversity of skills acquired during the PhD for a wide range of careers.
DGtal release 1.2
DGtal is an open source C++ library for the geometry processing of digital data (geometry processing on grids). The library has been managed at LIRIS since 2010 and thanks to a special support from the LIRIS, this new release contains a brand new python binding of the library.
- Theo Jaunet, Corentin Kervadec, Romain Vuillemot, Grigory Antipov, Moez Baccouche & Christian Wolf (2021). « VisQA: X-raying Vision and Language Reasoning in Transformers ». IEEE Transactions on Visualization and Computer Graphics. HAL : hal-03293079.
- Alexandre Millot, Rémy Cazabet & Jean-François Boulicaut (2021). « Exceptional Model Mining meets Multi-objective Optimization ». 2021 SIAM International Conference on Data Mining (SDM), 29 avril 2021, Alexandria ( virtual event ) (États-Unis), pp. 378-386. doi : 10.1137/1.9781611976700.43. HAL : hal-03220671.
- Besma Khalfoun, Sonia Ben Mokhtar, Sara Bouchenak & Vlad Nitu (2021). « EDEN: Enforcing Location Privacy through Re-identification Risk Assessment: A Federated Learning Approach ». Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 5, n°2, p. 68. doi : 10.1145/3463502. HAL : hal-03274635.
- Senda Romdhani, Genoveva Vargas-Solar, Nadia Bennani & Chirine Ghedira (2021). « QoS-based Trust Evaluation for Data Services as a Black Box ». INTERNATIONAL CONFERENCE ON WEB SERVICES, 10 septembre 2021, chicago (États-Unis). HAL : hal-03314992.
- Hamid Ladjal, Michael Beuve, Philippe Giraud & Shariat Behzad (2021). « Towards Non-invasive Lung Tumor Tracking Based on Patient-Specific Model of Respiratory System ». IEEE Transactions on Biomedical Engineering, vol. 68, n°9, pp. 2730-2740. doi : 10.1109/TBME.2021.3053321. HAL : hal-03113681.
- Axel Paris, Adrien Peytavie, Eric Guérin, Pauline Collon & Eric Galin (2021). « Synthesizing Geologically Coherent Cave Networks ». Computer Graphics Forum. HAL : hal-03331697.
LIRIS Seminar, Alexander Lex (Univ. Utah): Literate Visualization: Making Visual Analysis Sessions Reproducible and Reusable
On 19/10/2021 from 13:00 to 14:00. Place: Nautibus, C4
Interactive visualization is an important part of the data science process. It enables analysts to directly interact with the data, exploring it with minimal effort. Unlike code, however, an interactive visualization session is ephemeral and can't be easily shared, revisited, or reused. Computational notebooks, such as Jupyter Notebooks, R Markdown, or Observable are widely used in data science. These notebooks are an embodiment of Knuth's “Literate Programming”, where the logic of a program is explained in natural language, figures, and equations. As a consequence, they are both reproducible, and reusable. In this talk, I will sketch approaches to "Literate Visualization". I will show how we can leverage provenance data of an analysis session to create well-documented and annotated visualization stories that enable reproducibility and sharing. I will also introduce work on inferring analysis goals, which allows us to understand the analysis process at a higher level. Understanding analysis goals enables us to enhance interaction capabilities and even re-used visual analysis processes. I will conclude by demonstrating how this provenance data can be leveraged to bridge between computational and interactive environments.Read more… Partager