Some personal news: I will be joining @CompSciOxford @UniofOxford as @DeepMind chair in #AI and Fellow at @ExeterCollegeOx I owe this honour to the amazing students and collaborators with whom I have had the privilege to work during my career
I would like to thank the HoD Leslie Goldberg and former HoD @wooldridgemike for their support and patience that allowed this appointment to happen
I will remain the Head of GraphML at Twitter and will keep an honorary affiliation at Imperial where I have many amazing colleagues and exciting collaborations
I will be looking for new PhD students at @UniofOxford to work on geometric deep learning, GNNs, proteins, drug design, and sperm whale communication @ProjectCETI

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More from @mmbronstein

30 Nov
Over-squashing is a common plight of GNNs occurring when message passing fails to propagate information efficiently on the graph. In a new post, we discuss how this phenomenon can be understood and remedied through the concept of Ricci curvature

michael-bronstein.medium.com/over-squashing… Image
Collaboration between @TwitterEng #Cortex and @UniofOxford Jake Topping Francesco Di Giovanni @b_p_chamberlain Xiaowen Dong

Details in the paper: arxiv.org/pdf/2111.14522…
This is part of a new series on "GNNs through the lens of Differential Geometry and Algebraic Topology"

towardsdatascience.com/graph-neural-n…

(though in a different order I have initially promised :-)
Read 6 tweets
18 Nov
After a hiatus, a new series of blogs posts. Do differential geometry and algebraic topology sound too exotic for ML? In recent works, we show that tools from these fields bring a new perspective on graph neural networks

First post in the series:

towardsdatascience.com/graph-neural-n…
Based on recent works with @CristianBodnar @ffabffrasca @kneppkatt @wangyg85 @pl219_Cambridge @guidomontufar @b_p_chamberlain @migorinova @stefan_webb @emaros96 @aittalam James Rowbottom, Jake Topping, Xiaowen Dong, Francesco Di Giovanni
Cool animation of Cora graph evolution by James Rowbottom
Read 6 tweets
18 Mar
The recording of my #inaugural talk at @imperialcollege is now available online



This geometric view on deep learning is the convergence of many old and recent research threads and joint work with @joanbruna @PetarV_93 and @TacoCohen
Joan's 2014 paper on spectral #graphneuralnetworks was my inspiration to get into this field and write our paper with him, @ylecun @trekkinglemon and Arthur Szlam that popularized the term #geometricdeeplearning
Some of the works I mention are due to my amazing students and colleagues @jonathanmasci Davide Boscaini @EmanueleRodola @befcorreia Pablo Gainza @FreyrSverrisson @emaros96 @ffabffrasca @gbouritsas @frederickmonti @b_p_chamberlain @aittalam Kirill Veselkov Guadalupe Gonzalez
Read 10 tweets
4 Jan
In summer 2020, I started writing a blog on #GraphML in @TDataScience

towardsdatascience.com/graph-deep-lea…

It was a new and rewarding experience, from which I learned a lot. I was surprised that such a technical topic would attract >200K views and >6K claps in less than half a year. Image
I am grateful to all the readers and colleagues whom I used as "guinea pigs" to proof-read my posts especially @frederickmonti @emaros96 @b_p_chamberlain @ffabffrasca @gbouritsas @__lucab @fhuszar and to @kmborgwardt @thomaskipf @guennemann whose comments helped improve them
The first post was based on a seminar I gave for the @IEEEsps on the successes and challenges of #GraphML and #geometricdeeplearning

towardsdatascience.com/deep-learning-…
Read 9 tweets

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