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SUMMARY:IP Paris Seminar on Incentives and Computation
DESCRIPTION:The IP Paris Seminar on Incentives and Computation brings together researchers working at the intersection of economics and computer science to explore how incentives and strategic behavior shape large-scale computational systems. \nThe first session of the 2026–2027 series will feature Jason Hartline (Northwestern University) with a talk titled “Scoring Rules and Foundations of AI.” \nThe seminar covers topics including mechanism and market design\, computational economics and finance\, algorithmic game theory\, distributed algorithms\, cryptoeconomics\, agentic AI\, and alignment. \nThe session is open to faculty\, postdocs\, PhD students\, and colleagues from other institutions. No registration is required. \n\n\n\n\n\n\n\n\n\nMore information: https://ipparis-seminar.github.io/
URL:https://hi-paris.fr/event/ip-paris-seminar-on-incentives-and-computation/
LOCATION:Bâtiment d’Enseignement Mutualisé (BEM)\, Avenue Augustin Fresnel\, Palaiseau\, 91120\, France
CATEGORIES:Research
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DTSTAMP:20260529T102028Z
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SUMMARY:Hi! PARIS Exceptional Seminar - “Geometric Machine Learning for ML Probabilistic Weather Prediction” by Boris Bonev (NVIDIA)
DESCRIPTION:Hi! PARIS is pleased to welcome Boris Bonev\, Research Scientist at NVIDIA\, for an exceptional scientific seminar. \nHis talk\, titled “Geometric Machine Learning for ML Probabilistic Weather Prediction\,” will explore how geometric machine learning can support the next generation of weather and climate forecasting systems. As machine learning models become increasingly powerful tools for numerical weather prediction\, key challenges remain\, especially when dealing with extreme events\, spherical Earth geometry\, grid resolution\, and long-term stability. \nBoris Bonev will present recent advances in geometric neural operators designed to respect the symmetries and topology of the sphere. The seminar will focus on methods such as the Spherical Fourier Neural Operator\, spherical attention mechanisms\, and their application to atmospheric dynamics. He will also discuss FourCastNet 3\, a scalable probabilistic weather forecasting system developed with spherical signal-processing principles and trained on large-scale GPU infrastructure. \nThe seminar will highlight how these approaches can deliver faster\, more stable\, and more physically consistent forecasts\, opening new perspectives for weather prediction\, climate modeling\, and downscaling systems. \nAbout the speaker\nBoris Bonev is a Research Scientist at NVIDIA\, where he works on machine learning and numerical algorithms. His research focuses on applying mathematics and computational methods to complex scientific and engineering problems\, including scientific computing\, numerical simulation\, and machine learning for scientific applications. He holds a Ph.D. in Applied Mathematics from EPFL\, completed under the supervision of Jan S. Hesthaven. \nRegister here!
URL:https://hi-paris.fr/event/hi-paris-exceptional-seminar-geometric-machine-learning-for-ml-probabilistic-weather-prediction-by-boris-bonev-nvidia/
LOCATION:Bâtiment d’Enseignement Mutualisé (BEM)\, Avenue Augustin Fresnel\, Palaiseau\, 91120\, France
CATEGORIES:Research
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