Language and Learning
Calendar of Events
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1 event,
Diffusion Models Beat GANs? – Eliya Nachmani (TAU & FAIR)
Diffusion Models Beat GANs? – Eliya Nachmani (TAU & FAIR)
Recording: https://us02web.zoom.us/rec/share/AJjsXIl29nyD0ZSbadWHFd54QJFAB8sfV0b1WdcSY-kMvJE68rmdk595OO_yCUoK.f4P_M3-T4nfR5h91 Eliya Nachmani from TAU & FAIR. Title: Diffusion Models Beat GANs? Abstract: I will give a short introduction to generative diffusion models and present their performance compared to other generative models (including GANs). Moreover, I will present two works that we did in the last year: (i) Noise Estimation for Generative Diffusion Models: ... Read more
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Marginal Contribution Feature Importance – an Axiomatic Approach for Explaining Data. Amnon Catav (TAU).
Marginal Contribution Feature Importance – an Axiomatic Approach for Explaining Data. Amnon Catav (TAU).
The recording of Amnon's talk: https://us02web.zoom.us/rec/share/TxC7tgud-XyP-h577Pa-EwhLt9Bi4P7BCurUbafwRuW_-UiCxJDG8L9gAJylLiU4.OMMHDUVzuEc4ZVnE?startTime=1636279531000 Title: Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data Abstract: In recent years, methods were proposed for assigning feature importance scores to measure the contribution of individual features. While in some cases the goal is to understand a specific model, in many cases the goal is ... Read more