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

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

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

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

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 Bayesian Learning Rule', by Mohammad Emtiyaz Khan, Håvard Rue.

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

#bayesian #gradients #gradient

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

This introductory #MachineLearning book by John Winn has been in writing for a long time, and I am so pleased to see that it is finally published. Highly recommended for you to share with your colleagues who want to understand conceptually the meaning of fancy words in machine learning.

Model Based Machine Learning
https://mbmlbook.com/

An honour to give a keynote @icmlconf this year 🙏🏾 Video is now online and I’m eager to probe further into this topic of Machine learning with social purpose. Talk in 3 parts: earth systems, Sociotechnical, & global AI. Would love your views 🎈#ICML2023 https://icml.cc/virtual/2023/invited-talk/21547

Very honoured to be included in this year’s #Time100AI list of influential people in AI🎈And more so the humbling messages from so many people ❤️. The work on directing AI to social purpose remains, and the ownership and inclusion of global communities🌍 https://time.com/collection/time100-ai/6311118/shakir-mohamed/

Honored to be on this list with many of my friends & colleagues. And as usual, also along with some of the worst people. May their influence wane.
I was especially happy to see the crucial work of content moderators like Richard Mathenge being recognized.

https://time.com/collection/time100-ai/6308980/richard-mathenge/

Faster Training of Neural ODEs Using Gauß–Legendre Quadrature

Alexander Luke Ian Norcliffe, Marc Peter Deisenroth

Action editor: Kevin Swersky.

https://openreview.net/forum?id=f0FSDAy1bU

#odes #models #quadrature

@tmlrpub
This work is based on Alex Norcliffe's MSc thesis. It's about faster training of Neural ODEs.

Main point: Training Neural ODEs done via the adjoint method boils down to solving 1D integrals. We propose to use Gaussian quadrature instead of ODE solvers to do this, which gives us a good speed-up while retaining good gradient estimates.

We apply the same ideas to faster training of Neural SDEs.

Paper: https://t.co/sSV7G2lwMW
Code: https://t.co/nv2sGMcRmt
Video: https://t.co/eXkLGs7ovU

#ICML2023 test of time award (most impactful papers from in #MachineLearning from ICML 2013):
https://icml.cc/Conferences/2023/Test-of-Time

- Learning Fair Representations - which started a whole new subfield (shameless plug that Sevvandi has a #Job #Opening for a #postdoc in #Australia https://jobs.csiro.au/job/Melbourne%2C-VIC-CSIRO-Postdoctoral-Fellowship-in-Fairness-Research-in-Machine-Learning-%28FairML%29/941838510/)

The two runner ups:
- multimodal representation learning
- AutoML, hyperparameter search.

Had an energising time at the United Nations University @UNUniversity HQ in Tokyo 🇺🇳, meeting the community invested in the future of AI, and talking through topics on SDG attainment, AI, governance, risks, opportunities and more. Thanks to Sabine, Nicholas, Tshilidzi, @deisenroth 🎉

Regular reminder of the best mathematical resource in #machinelearning, The Matrix Cookbook. Don't know how anyone ever does any math without it. https://www.math.uwaterloo.ca/~hwolkowi/matrixcookbook.pdf

I am very concerned about the future of AI. Not because of the risk of rogue machines taking over. But because of the homogeneous, one dimensional group of men who are currently involved in advancing the technology.

Concerned AI researcher