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DTSTART;TZID=Europe/Paris:20260602T140000
DTEND;TZID=Europe/Paris:20260602T150000
DTSTAMP:20260704T204427
CREATED:20260527T104943Z
LAST-MODIFIED: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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ORGANIZER;CN="Hi! PARIS":MAILTO:contact@hi-paris.fr
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20260610T150000
DTEND;TZID=Europe/Paris:20260610T163000
DTSTAMP:20260704T204427
CREATED:20260601T095102Z
LAST-MODIFIED:20260601T095102Z
UID:10000027-1781103600-1781109000@hi-paris.fr
SUMMARY:ELIAS Series on AI & Sustainability: Spotlight on Diverse Career Trajectories
DESCRIPTION:ELIAS Series is a seminar series designed specifically to support junior researchers by exploring diverse career paths within the double scope of Sustainable AI and AI for Sustainability. This first session is on AI & Sustainability: Spotlight on Diverse Career Trajectories. \n Speaker: Claire Monteleoni (AI Research for Climate Change and Environmental Sustainability – INRIA Paris) \nTalk: Generative AI for Climate and Weather \nThe stunning recent advances in frontier AI models rely on cutting-edge\, generative deep learning algorithms and architectures trained on massive amounts of text\, image\, and video data. With different training data\, these algorithms and architectures can benefit a variety of applications for addressing climate change. As opposed to text and video\, the relevant training data includes weather and climate data from observations\, reanalyses\, and even physical simulations. \nMany applications aimed at addressing climate change hinge on fundamental challenges of data fusion\, interpolation\, downscaling\, and probabilistic domain alignment. Claire Monteleoni will provide a survey of recent work developing generative AI methods for these problems\, with applications including weather forecasting\, climate model emulation and scenario interpolation\, and renewable energy planning. \n Register here!
URL:https://hi-paris.fr/event/elias-series-on-ai-sustainability-spotlight-on-diverse-career-trajectories-2/
CATEGORIES:Research,Society
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DTSTART;TZID=Europe/Paris:20260618T110000
DTEND;TZID=Europe/Paris:20260618T120000
DTSTAMP:20260704T204427
CREATED:20260527T103835Z
LAST-MODIFIED:20260527T110002Z
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SUMMARY:Hi! PARIS Exceptional Seminar - “How to Design Fast GFTs” by Antonio Ortega\, University of Southern California
DESCRIPTION:Hi! PARIS is pleased to welcome Antonio Ortega\, Professor of Electrical and Computer Engineering at the University of Southern California\, for a scientific seminar organized in the framework of the Hi! PARIS International Visiting Chairs Program. \nHis talk\, titled “How to Design Fast GFTs\,” will provide an overview of recent advances in speeding up the computation of the Graph Fourier Transform\, also known as GFT. \nGraph Fourier Transforms play an important role in graph signal processing\, with applications in image and video coding\, graph machine learning\, multimedia compression\, 3D point cloud processing\, and sensor networks. However\, computing these transforms efficiently remains a key challenge\, especially for large or complex graph structures. \nAntonio Ortega will present divide-and-conquer techniques that make use of graph structure\, including graph symmetries and graph decompositions based on low-rank updates. He will also discuss approximation methods for cases where the graph structure alone does not provide enough acceleration. These include direct transform approximations using Givens rotations\, as well as indirect methods that rely on more favorable graph structures\, such as spectral sparsification. \nThe seminar will highlight how these approaches can improve the efficiency of graph-based signal processing methods and support applications in image and video coding\, graph machine learning\, and related fields. \nAbout the speaker \nAntonio Ortega is Professor of Electrical and Computer Engineering at the University of Southern California. He is a Fellow of the IEEE and EURASIP\, and currently serves as Vice President of Publications of the IEEE Signal Processing Society. \nHis research focuses on graph signal processing\, including sampling\, reconstruction\, transforms\, learning\, and compression\, as well as multimedia and 3D point cloud compression\, distributed and error-tolerant compression\, and information representation in sensor networks. \nHe has supervised nearly 50 Ph.D. students\, authored more than 400 publications\, and published the book Introduction to Graph Signal Processing with Cambridge University Press in 2022. His work has received several distinctions\, including the IEEE Signal Processing Magazine Award\, the ICIP Best Paper Award\, and the IEEE Communications Society Leonard G. Abraham Prize. \nRegister here!
URL:https://hi-paris.fr/event/hi-paris-exceptional-seminar-how-to-design-fast-gfts-by-antonio-ortega-university-of-southern-california/
LOCATION:Télécom Paris\, 19 Pl. Marguerite Perey\, Palaiseau\, 91120\, France
CATEGORIES:Research
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ORGANIZER;CN="Hi! PARIS":MAILTO:contact@hi-paris.fr
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