Topics: This seminar series aims to explore the full range of artificial intelligence topics represented within Hi!PARIS, with a particular focus on theoretical aspects to reach a broad scientific audience. We invite specialists from various fields — self-supervised learning, computer vision, statistics, machine learning, large language models (LLMs), and more — to present their work. The series is primarily intended for PhD students in AI but remains open to anyone with prior knowledge of artificial intelligence.
Place and dates: The seminar takes place on the first Wednesday of each month from 11 a.m. to 12 p.m. Some sessions are held in a hybrid format (in-person and online), while others take place exclusively via videoconference. The Zoom link is provided upon request through the Hi!PARIS form.
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Topics: This colloquium is organized around data sciences in a broad sense with the goal of bringing together researchers with diverse backgrounds (including for instance mathematics, computer science, physics, chemistry and neuroscience) but a common interest in dealing with large scale or high dimensional data.
Place and dates: the colloquium takes place one a month in the ENS building (45 rue d'Ulm).
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Topics: The mission of the HPC for Learning GT (within the CNRS GDR C4P) is to build a collaborative community at the crossroads of AI and HPC, co-designing algorithms and architectures for scalable training, memory/communication-efficient learning, accelerator-optimized algorithms, and robust, reproducible inference on modern hardware.
Place and dates:  SCAI (Sorbonne University)
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