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Yarin
@yaringal
Professor of Machine Learning, University of Oxford @OATML_Oxford Group Leader Expert Advisor to AISI "One of the top machine-learning people" - Tim Berners-Lee
Oxford, England
Joined February 2014
Posts
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    Really excited to release Bayesian Deep Learning Benchmarks - please share with others who you think might like this, and have a look at the blog/repo/colab: github.com/OATML/bdl-benc… This work was done over a period of a year and a half by many collaborators @OATML_Oxford
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    I'm hiring! I'm building 4 research groups under me at AISI (formerly the UK's Taskforce on Frontier AI) to work on foundational AI safety research. [1/5]
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    All the slides from my Bayesian Deep Learning tutorial at MLSS 2019 Moscow, including a practical in Active Learning with jupyter notebooks (practical credit: Ivan Nazarov), are now online bdl101.ml
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    New blog post! "Uncertainty in Deep Learning" - also my PhD thesis and lots of new results mlg.eng.cam.ac.uk/yarin/blog_224…
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    I really like blog posts which try to teach the reader old ideas. This one is about ways to visualise concepts in information theory, mentioned (cautiously) in solution 8.8 in Mackay's book (remember, positive areas can be negative quantities!) By @BlackHC
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    Did you know that you can beat Deep Ensemble Uncertainty with a single deterministic net? We prove that softmax nets can't normally capture epistemic uncertainty, but with an appropriate inductive bias any pre-trained net can implicitly capture uncertainty arxiv.org/abs/2102.11582
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    I'm looking for PhD applicants who have expertise in Gaussian processes and/or Transformers for an exciting PhD project If this sounds interesting, application deadline for funding is 3/12 Please share with people you think this might be relevant to!
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    Dear research community, please keep machine learning open access @NipsConference @icmlconf @iclr2017 JMLR
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    Very happy to be named one of MIT Technology Review @techreview Europe's 35 under 35. Many thanks to all my collaborators over the years! innovatorsunder35.com/the-list/yarin…
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    We're looking for PhD students to join @OATML_Oxford! We work on topics such as developing Bayesian deep learning methodology, applications of ML, AI security, and understanding ML methodology. A fully funded scholarship opportunity to work with us:
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    This year's #BDL workshop at @NeurIPSConf will focus on the reliability of BDL in downstream tasks, with invited talks from practitioners and the two NeurIPS BDL challenges bayesiandeeplearning.org Please consider submitting extended abstracts by Oct 1, or posters by Dec 1
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    Our car below never saw roundabouts at training time. But using dropout ensembles' epistemic uncertainty we can choose the best worst-case plan to follow at deployment We put code online to make it as easy as MNIST to plug & play your own BDL tools: github.com/OATML/oatomobi…
    Can autonomous 🚘 identify, recover from, and adapt to distribution shifts? We play with BDL and robust control to get cars to recover&adapt when they don't know what to do At ICML with @filangelos @ptigas @rowantmc @nick_rhinehart @svlevine 📄🎞️🕸️💻: oatml.cs.ox.ac.uk/blog/2020/07/0…
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    The Bayesian Deep Learning workshop website has been updated with accepted papers and schedule #BDL2019 bayesiandeeplearning.org
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    Bayesian neural networks uncertainty can be used to distinguish adversarial from non-adversarial images! new results mlg.eng.cam.ac.uk/yarin/publicat…