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  2. Machine Learning 4f13 Lent 2011

    https://mlg.eng.cam.ac.uk/teaching/4f13/1011/
    19 Nov 2023: Feb 22, 24. Variational approximations (2L): KL divergences, mean field, expectation propagation.
  3. Machine Learning 4f13 Lent 2010

    https://mlg.eng.cam.ac.uk/teaching/4f13/0910/
    19 Nov 2023: Feb 24, 25. Model comparison (1L): Bayes factors, Occam's razor, BIC, Laplace approximations.
  4. Machine Learning 4f13 Lent 2014

    https://mlg.eng.cam.ac.uk/teaching/4f13/1314/
    19 Nov 2023: Feb 3, 6, 10, 13. Probabilistic Ranking. Feb 17, 20, 24, 27, Mar 3, 6.
  5. 27 Jan 2023: Week 14/15 (April 24, 29, May 1). Model Selection. Bayes Factors.
  6. June

    https://mlg.eng.cam.ac.uk/carl/climate/1tonCO2.pdf
    4 Jul 2024: June 24, 2024 1 / 1.
  7. 19 Jun 2024: 100. Maximum coupling strength y. BethelocalBethecycleBethemargTRWlocalTRWcycleTRWmarg. log partition error. 2 8 16 24 320. ... 2 8 16 24 320. 0.1. 0.2. 0.3. 0.4. Maximum coupling strength y.
  8. Alex Matthews awarded by Google for his work on TensorFlow |…

    https://mlg.eng.cam.ac.uk/news/alex-matthews-awarded-by-google-for-his-work-on-tensorflow/
    3 Jul 2024: Search. Alex Matthews awarded by Google for his work on TensorFlow. Alex Matthews has been given a software award from the Google Open Source Programs Office for his work on TensorFlow. The award is for “…people outside of Google that they
  9. 13 Feb 2023: Publications, Machine Learning Group, Department of Engineering, Cambridge. current group:. [former members:. [by year:. [2022. James Urquhart Allingham, Florian Wenzel, Zelda E Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel,
  10. Natural-Gradient Variational Inference 2: ImageNet-scale · Cambridge…

    https://mlg.eng.cam.ac.uk/blog/2021/11/24/ngvi-bnns-part-2.html
    12 Apr 2024: Published on 24 November 2021. This is the blog of the Cambridge Machine Learning Group.
  11. Machine Learning Group Publications

    https://mlg.eng.cam.ac.uk/pub/topics/
    13 Feb 2023: Publications, Machine Learning Group, Department of Engineering, Cambridge. current group:. [former members:. [by year:. [Gaussian Processes and Kernel Methods. Gaussian processes are non-parametric distributions useful for doing Bayesian inference

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