Surprisingly, @RealAAAI chairs updated my review without my permission. I never experienced this before, and now I have to rethink whether I will submit to or review for this conference again.
Wonder about people's opinion on this: https://t.co/FkRplD8zT1
Price is half of G-suite, 1/3 of Slack's.
Would you use this brought by a Chinese unicorn company?
By far the cleanest and most elegant library for graph neural networks in PyTorch. Highly recommended! Unifies Capsule Nets (GNNs on bipartite graphs) and Transformers (GCNs with attention on fully-connected graphs) in a single API.
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations—learning a dependency graph to do deep transfer learning. Jake Zhao: “Perhaps this can also be seen as encoding some relational inductive bias into the machinery” 🤔 https://t.co/TkN7y3XDQb HT @ylecun
Guided evolutionary strategies: escaping the curse of dimensionality in random search. A principled method to leverage training signals which are not the gradient, but which may be correlated with the gradient. Work with @niru_m@Luke_Metz@georgejtucker. https://t.co/LNPHDUrDFu