An excellent talk on the emerging topic of geometrical deep learning - this could bring topological data analysis which we did for decades to new importance!
Nice lecture! “Attention is all you need.” - Is that also true for GNNs? Can dynamic graph networks be used to predict chemical reaction outcomes or yields or retrosynthetic pathways? The secret sauce of autogluon tabular is bagging, stacking and destillation. How to apply destillation on graph neural networks?
One thing that’s always confuse me is that seems (or in any example I found) with node/link prediction the whole dataset is a single graph. Is it possible to train/predict with different graphs?
An excellent talk on the emerging topic of geometrical deep learning - this could bring topological data analysis which we did for decades to new importance!
This talk provides a helpful understanding of the intuition behind the speaker's work on geometric deep learning. Great talk! Thank you.
Man, this is a Masterpiece.
Thank you for sharing.
great talk, such a generous share
Amazing talk! I learned a lot and got some ideas for my research. Cheers!
Fantastic talk! Thanks for sharing!
Nice lecture!
“Attention is all you need.” - Is that also true for GNNs?
Can dynamic graph networks be used to predict chemical reaction outcomes or yields or retrosynthetic pathways?
The secret sauce of autogluon tabular is bagging, stacking and destillation. How to apply destillation on graph neural networks?
Well regarding attention I would look up GAT (Graphical Attention Networks)
Awesome lecture thanks!!
One thing that’s always confuse me is that seems (or in any example I found) with node/link prediction the whole dataset is a single graph. Is it possible to train/predict with different graphs?
Thanks super powerful.
Yup, food is medicine, many of us overlook this fundamental property. Eat right and the likelihood of illness diminishes exponentially
Great talk!
Gold
41:45 It was a bunny mesh oirc
*iirc
I love how carefully picking samples expedites the training time! Great idea that may be applicable in other situations!
oh I was wondering how all those 3d AI things worked
Hi
I didn't even need to see the bunny to be pretty sure it must be a bunny. Most animal meshes in academia are bunnies.
Applying Bayes' naive rule, eh?😜
This is who you want to be getting your geometry from hahahahaha