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1 - 10 of 210 search results for TALK:PC53 20 |u:mlg.eng.cam.ac.uk where 0 match all words and 210 match some words.

  1. Results that match 1 of 2 words

  2. Posts by Tag · Cambridge MLG Blog

    https://mlg.eng.cam.ac.uk/blog/posts-by-tag
    12 Apr 2024: Diffusion Model. 20 January 2024. An introduction to Flow Matching. ByFlow matching (FM) is a new generative modelling paradigm which is rapidly gaining popularity in the deep learning community. ... Pierre-Simon Laplace (1749–1827). Generative

  3. Machine Learning 4f13 Lent 2009

    https://mlg.eng.cam.ac.uk/teaching/4f13/0809/
    19 Nov 2023: Jan 20, 23. Unsupervised learning (2L): factor analysis, PCA, the EM algorithm. ... Feb 17, 20. Variational approximations (2L): KL divergences, mean field, expectation propagation.

  4. Photo competition entries from the group featured in The Telegraph |…

    https://mlg.eng.cam.ac.uk/news/photo-competition-entries-from-the-group-featured-in-the-telegraph/
    3 Jul 2024: Nov 20, 2014. Two entries from the group into the 2014 Engineering Department Photo Competition are featured in The Telegraph.

  5. Uprooting and Rerooting Graphical Models

    https://mlg.eng.cam.ac.uk/adrian/puproot.pdf
    19 Jun 2024: 5. 10. 15. 20. 25Original MMworstmaxWmaxtWbest. maximum edge strength Wmax. 2 4 8 12 160. ... 20. 40. 60. 80. 100Original MMworstmaxWmaxtWbest. low singleton θi [0.1, 0.1] medium singleton θi [2, 2] singleton edge potentials scale together.

  6. Cambridge MLG Blog

    https://mlg.eng.cam.ac.uk/blog/
    12 Apr 2024: 20 January 2024. An introduction to Flow Matching. ByFlow matching (FM) is a new generative modelling paradigm which is rapidly gaining popularity in the deep learning community.

  7. Machine Learning 4f13 Lent 2014

    https://mlg.eng.cam.ac.uk/teaching/4f13/1314/
    19 Nov 2023: Jan 16, 20. Introduction to Machine Learning(2L):. the concept of a model, linear in the parameters regression: makaing predictions, least squares fit, overfitting. ... Feb 3, 6, 10, 13. Probabilistic Ranking. Feb 17, 20, 24, 27, Mar 3, 6.

  8. Understanding the Bethe Approximation: When and How can it go Wrong?

    https://mlg.eng.cam.ac.uk/adrian/pabc.pdf
    19 Jun 2024: true values. 2 8 16 24 320. 20. 40. 60. 80.

  9. Machine Learning 4f13 Lent 2008

    https://mlg.eng.cam.ac.uk/teaching/4f13/0708/
    19 Nov 2023: Feb 20, 22. Variational approximations (2L): KL divergences, mean field, expectation propagation.

  10. Machine Learning 4f13 Lent 2012

    https://mlg.eng.cam.ac.uk/teaching/4f13/1112/
    19 Nov 2023: Jan 26, 30 and Feb 2nd. Gaussian processes (3L):. Feb 6, 9, 13, 16 and 20.

  11. Machine Learning 4f13 Lent 2011

    https://mlg.eng.cam.ac.uk/teaching/4f13/1011/
    19 Nov 2023: LECTURE SYLLABUS. Jan 20 . Introduction to Machine Learning(1L): review of probabilistic models, relation to coding terminology: Bayes rule, supervised, unsupervised and reinforcement learning.

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