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Posts with #normalizingflows

#normalizingflows

Public posts on X that use #normalizingflows.

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  4. Claudius Krause@ClaudiusKrause
    Pre Christmas #HEPML papers, part 2. Together with Florian Ernst, Luigi Favaro, Tilman Plehn, and David Shih, we investigate how we can go beyond CaloFlow and scale #NormalizingFlows up to high-dimensional #Calorimeter data, while still being really fast in generation. 1/5
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  5. Shirley Ho✓@cosmo_shirley
    Using #normalizingflows for #GravitationalWaves population analysis! [Left]: using normalizing flow for the likelihood. [Right]: using analytic likelihood. But you can make normalizing flow likelihood from training data w/o analytical assumptions
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  6. ML Group, TU Berlin@ml_tuberlin
    🔉 Check out the camera ready version of the #ICLR2024 paper by @LVaitl @ludiXIVwinkler @lorenz_richter and @daspantom in collaboration with @bifoldberlin @ZuseInstitute @dida_ML and @PrescientDesign! #MachineLearning #NormalizingFlows
    Lorenz Vaitl @LVaitl
    We're excited to present our paper "Fast and Unified Path Gradient Estimators for Normalizing Flows" at #ICLR2024 in two weeks! 🎉 This work focuses on deriving efficient gradient estimators for coupling-type normalizing flows using the inverse function theorem.
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  7. Lorenz Vaitl@LVaitl
    We're excited to present our paper "Fast and Unified Path Gradient Estimators for Normalizing Flows" at #ICLR2024 in two weeks! 🎉 This work focuses on deriving efficient gradient estimators for coupling-type normalizing flows using the inverse function theorem.
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  10. Pablo Sánchez@ML_pablosm
    👀 Curious about how to answering causal queries of mixed-type data? 🎯 Don't miss our latest work! We provide an answer to such question and much much more! 🧵Check out the amazing thread by @javaloyML #NormalizingFlows #CausalInference
    Adrián Javaloy @javaloyML
    Hi! I am happy to announce our latest work (with @ML_pablosm and @IValeraM) ... 🥁 🚨 Causal normalizing flows: from theory to practice 🚨 I am really excited about this work! Check this image, and scroll down if you want to know more 👀 1/10
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  11. Adrián Javaloy@javaloyML
    Hi! I am happy to announce our latest work (with @ML_pablosm and @IValeraM) ... 🥁 🚨 Causal normalizing flows: from theory to practice 🚨 I am really excited about this work! Check this image, and scroll down if you want to know more 👀 1/10
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    2179230.8K
  21. Steve Kroon@skroon
    Thanks to @JaneStreetGroup and @DepthFirstLearn for this exciting initiative! I'm looking forward to exploring @shakir_za and @DeepSpiker's #normalizingflows with enthusiastic students - sign up if you're interested in this or one of the other groups at
    Depth First Learning @DepthFirstLearn
    We are super proud to announce the 2019 DFL Jane Street Fellows! They will each be leading a group towards deeply understanding a machine learning paper and its associated topics. In palindromic order, they (and their target papers) are:
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  22. Depth First Learning@DepthFirstLearn
    We are super proud to announce the 2019 DFL Jane Street Fellows! They will each be leading a group towards deeply understanding a machine learning paper and its associated topics. In palindromic order, they (and their target papers) are:
    2642
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