Marc Deisenroth

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Machine learning researcher | Professor at UCL | he/him | šŸ³ļøā€šŸŒˆ
Personal websitehttps://deisenroth.cc
MML Bookhttps://mml-book.com
Research group websitehttps://sml-group.cc
At The Alan Turing Institute, we are working with Open Climate Fix on AI for cloud now casting to predict the energy generation of solar panels. This project, a finalist of the Manchester Prize, aligns with our aim to use AI and data science to tackle the most pressing societal issues. In the coming years, optimising and forecasting the use of renewable energy is going to be crucial to ensure that our management of these vital energy sources is efficient and helps us to decarbonise faster.

This spring, the "crazy off-by-one weeks" period is three weeks long. The time between the US change to daylight saving until the EU switches. All US<=>Euro meetings are off by one hour during this period.

Starts now, ends on March 31. The perfect excuse to miss out on selected most boring meetings =)

'Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees', by Alexander Terenin et al.

http://jmlr.org/papers/v25/22-1170.html

#interpolation #sparse #gaussian

Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees

The "User-friendly Introduction to PAC-Bayes Bounds" by my friend Pierre Alquier is now officially published! I strongly recommend it if you want to know what PAC-Bayes is about. You can purchase it or download a free version here (you can also find it on arxiv):

https://nowpublishers.com/article/Details/MAL-100

now publishers - User-friendly Introduction to PAC-Bayes Bounds

Publishers of Foundations and Trends, making research accessible

I’m happy to share that I’m starting a new position as Director of Science and Innovation---Grand Challenges (Environment & Sustainability) at The Alan Turing Institute.

https://www.turing.ac.uk/news/turing-appoints-four-directors-address-societys-biggest-challenges-through-data-science-and-ai

If you liked our ( @deisenroth Aldo Faisal, and me) #Mathematics for #MachineLearning book
https://mml-book.com
(PDF freely downloadable)

and want to have a hard copy, you can get a 30% discount this month on the publisher's website as part of #neurips2023 .

https://www.cambridge.org/us/universitypress/conferences/neural-information-processing-systems3/

Discount code: 101868

Mathematics for Machine Learning

Companion webpage to the book ā€œMathematics for Machine Learningā€. Copyright 2020 by Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. Published by Cambridge University Press.

Mathematics for Machine Learning
Are you a senior researcher who would like to visit Oxford (for up to a year) to work on the **Governance of AI**? We have a post for you! Applications are due **24 November**
https://my.corehr.com/pls/uoxrecruit/erq_jobspec_version_4.display_form?p_company=10&p_internal_external=E&p_display_in_irish=N&p_process_type=&p_applicant_no=&p_form_profile_detail=&p_display_apply_ind=Y&p_refresh_search=Y&p_recruitment_id=168678
Job Details

Superb from @chrischirp on the lessons we should have learned during pandemic, the implications of this and an important question- why is Covid enquiry NOT looking more closely at events in the summer and beyond 2020? https://www.newstatesman.com/spotlight/healthcare/2023/11/the-covid-inquiry-government-duty-failed
The Covid inquiry has laid bare the government’s dereliction of duty

The aftermath of the first lockdown in 2020 was an opportunity to make choices, to learn from the global experience of the first months of the pandemic, and to plan for the coming winter. Serious peop

New Statesman

'The Bayesian Learning Rule', by Mohammad Emtiyaz Khan, HƄvard Rue.

http://jmlr.org/papers/v24/22-0291.html

#bayesian #gradients #gradient

The Bayesian Learning Rule

Good news from the ELISE network for scientists planning a research stay in another lab or who would like to host a researcher for a short/long-term visit: ELISE mobility funding is now also available for researchers outside the ELLIS/ELISE network!

Find all details and the guidelines for application here: https://www.elise-ai.eu/work/researcher-mobility

#machinelearning #mobilityprogram #researchcollaboration

Researcher-Mobility

ELISE is a network of artificial intelligence research hubs. Based on the highest level research, it spreads its knowledge and methods in academia, industry and society. The network invites all ways of reasoning, considering all types of data, applicable for almost all sectors of science and industry. We do this while being aware of data safety and security and striving to explainable and trustworthy outcomes.