![]() |
You need to be logged in to carry this out. If you don't have an account, feel free to create one. |
COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. | ![]() |
University of Cambridge > Talks.cam > Theoretical Physics Colloquium > Transforming Particle Physics with AI
Transforming Particle Physics with AIAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Amanda Stagg. LHC as one of the most data-intensive scientific endeavors provides the perfect link between fundamental physics research and modern data science. As machine learning is transforming our lives, literally, no aspect of LHC physics is left untouched. This starts with identifying data for classic or optimal analyses and extends to anomaly searches and powerful simulations based on perturbative quantum field theory. I will give a few examples for the transformative power of modern machine learning in particle physics, show how our understanding of uncertainties adds new flavors to machine learning, and explain how generative neural networks allow us to realize our dream of making LHC data available to a broad scientific community. This talk is part of the Theoretical Physics Colloquium series. This talk is included in these lists:
Note that ex-directory lists are not shown. |
Other listsSoclikes 7th Annual Building Bridges in Medical Sciences best pgdm colleges in bangaloreOther talksTechnological pathways for thermomechanical energy conversion and storage: Progress, challenges and outlook Wearable electrocardiography: from Holter to handheld devices Chemical Looping Technology for Clean Energy and Chemical Conversion Systems – Commercialization Prospect Degree and dosage: rationalising therapy in the Long Renaissance (1300–1550) A Non-Equilibrium Transport Sampler Enlightenment Scepticism and the Conditions for Political Stability |