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Kandungan disediakan oleh The Thesis Review and Sean Welleck. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh The Thesis Review and Sean Welleck atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.
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[21] Michela Paganini - Machine Learning Solutions for High Energy Physics
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Kandungan disediakan oleh The Thesis Review and Sean Welleck. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh The Thesis Review and Sean Welleck atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.
Michela Paganini is a Research Scientist at DeepMind. Her research focuses on investigating ways to compress and scale up neural networks. Michela's PhD thesis is titled "Machine Learning Solutions for High Energy Physics", which she completed in 2019 at Yale University. We discuss her PhD work on deep learning for high energy physics, including jet tagging and fast simulation for the ATLAS experiment at the Large Hadron Collider, and the intersection of machine learning and physics. Episode notes: https://cs.nyu.edu/~welleck/episode21.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
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47 episod
MP3•Laman utama episod
Manage episode 302418424 series 2982803
Kandungan disediakan oleh The Thesis Review and Sean Welleck. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh The Thesis Review and Sean Welleck atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.
Michela Paganini is a Research Scientist at DeepMind. Her research focuses on investigating ways to compress and scale up neural networks. Michela's PhD thesis is titled "Machine Learning Solutions for High Energy Physics", which she completed in 2019 at Yale University. We discuss her PhD work on deep learning for high energy physics, including jet tagging and fast simulation for the ATLAS experiment at the Large Hadron Collider, and the intersection of machine learning and physics. Episode notes: https://cs.nyu.edu/~welleck/episode21.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
…
continue reading
47 episod
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