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Nikos Paragios – Seeing the Invisible – Doing the Impossible: Reinventing  Healthcare with Generative AI-powered diagnosis, treatment and beyond

Nikos Paragios – Seeing the Invisible – Doing the Impossible: Reinventing Healthcare with Generative AI-powered diagnosis, treatment and beyond

Nov 13, 2024 | 2024, diiP, Distinguished Lectures

Nikos ParagiosDecember 04, 2024Vulpian Amphitheater, 12 rue de l’École de Médecine (75006 Paris) 🔗 2024 diiP Projects Day Nikos Paragios (52) is distinguished professor of Mathematics (on partial leave) at Ecole CentraleSupelec, the school of engineering ofthe...
Alon Halevy – Well-being, AI, and You: Developing AI-based Technology for Well-being

Alon Halevy – Well-being, AI, and You: Developing AI-based Technology for Well-being

Oct 24, 2024 | 2024, diiP, Distinguished Lectures

Alon HalevyDecember 04, 2024Vulpian Amphitheater, 12 rue de l’École de Médecine (75006 Paris) 🔗 2024 diiP Projects Day Alon Halevy is a Distinguished Engineer in Google Cloud. From 2019 until November 2023, he was a director at Meta’s Reality Labs Research, where he...
Shen Liang – Knowledge-guided Data Science

Shen Liang – Knowledge-guided Data Science

Oct 24, 2024 | 2022, diiP, Seminars + Hands-On Workshops

Shen LiangMay 18, 4 PM online (zoom)   Follow Abstract This tutorial presents an overview of knowledge-guided data science, a rising methodology in machine learning which fuses data with domain knowledge. We will present numerous case studies on this methodology...
Shen Liang – Deep Transfer Learning and Multi-task Learning

Shen Liang – Deep Transfer Learning and Multi-task Learning

Oct 24, 2024 | 2022, diiP, Seminars + Hands-On Workshops

Shen LiangJune 15, 4 PMonline (zoom)     Follow Abstract This tutorial provides an overview of two important and correlated (in many cases intersectional) topics in deep learning: transfer learning, and multi-task learning. Transfer learning focuses on...
Foula Vagena – Deep Learning for Sequential Data: Models and Applications

Foula Vagena – Deep Learning for Sequential Data: Models and Applications

Oct 24, 2024 | 2021, diiP, Seminars + Hands-On Workshops

Foula VagenaApril 13, 4 PMonline (zoom)   Abstract Recurrent neural networks (RNNs) are a family of specialized neural networks for processing sequential data. They can scale to much longer sequences than would be practical for networks without sequence-based...
Foula Vagena – Ensemble Learning: Theory and Techniques

Foula Vagena – Ensemble Learning: Theory and Techniques

Oct 24, 2024 | 2021, diiP, Seminars + Hands-On Workshops

Foula VagenaDecember 15, 4pmonline (zoom)   Abstract Ensemble learning is the process by which multiple models, such as classifiers or experts, are combined to solve a particular computational intelligence problem. Ensemble learning is primarily used to improve...
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Recent Posts

  • Nikos Paragios – Seeing the Invisible – Doing the Impossible: Reinventing Healthcare with Generative AI-powered diagnosis, treatment and beyond
  • Deeply Learning from Neutrino Interactions with the KM3NeT neutrino telescope
  • Alon Halevy – Well-being, AI, and You: Developing AI-based Technology for Well-being
  • Shen Liang – Knowledge-guided Data Science
  • Shen Liang – Deep Transfer Learning and Multi-task Learning

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