Interested in geometric deep learning and dynamical systems. Former @twitterresearch intern. Beginning the PhD application cycle.

Joined July 2018
Replying to @tkipf
@thomaskipf and @wellingmax strike back! in a new blog post w/ @Francesco_dgv @_JRowbottom et al we show that GCN-type models can be derived as gradient flows of Dirichlet-type energy and provably avoid low-frequency dominated dynamics bit.ly/3TdhTLg
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This is a super accessible explanation* of our gradient flow work and it's based on a recent arXiv version contanining new theoretical results and experiments *Beware, great meme ahead
What new insights can we gain by leveraging physically-inspired approaches to graph neural networks? Don't miss the latest work from @mmbronstein and coauthors @Francesco_dgv, @b_p_chamberlain, @_JRowbottom, and @thomasmarkovich. buff.ly/3T1cCWU
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James Rowbottom retweeted
Here is last week's video of @Francesco_dgv, @_JRowbottom and @b_p_chamberlain presenting their paper "Graph Neural Networks as Gradient Flows"! youtu.be/sgTTtmwOMgE
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Equivariant Mesh Attention Networks Sourya Basu, Jose Gallego-Posada, Francesco Viganò, James Rowbottom, Taco Cohen openreview.net/forum?id=3Iqq…
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I am happy to share a recent work on energy functionals giving rise to GNN equations via gradient flows 🧵 arxiv.org/abs/2206.10991 This is joint work with @_JRowbottom*, @b_p_chamberlain, T. Markovich, and @mmbronstein
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1/4 Hope to see friends new & old tomorrow 4:30pm GMT / 8:30am PT poster session 6 #NeurIPS2021 @_JRowbottom @Francesco_dgv and I will occupy the prime virtual real estate known as Spot E3 with BLEND neurips.cc/virtual/2021/post…
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#GNNs are related to PDEs governing information diffusion on graphs. In a new paper with @b_p_chamberlain James Rowbottom @migorinova @stefan_webb @emaros96 we study a new class of Neural Graph Diffusion PDEs Blog post: bit.ly/3gUOEL8 Paper: arxiv.org/abs/2106.10934
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